Notes:
Support vector machines (SVMs) are a type of supervised machine learning algorithm that can be used for classification and regression tasks. They are based on the idea of finding the hyperplane in a high-dimensional space that maximally separates different classes.
In a classification task, an SVM algorithm will take a set of labeled training data and learn a model that can predict the class label of new, unseen data. The model is represented as a hyperplane in a high-dimensional space, and the goal is to find the hyperplane that maximally separates the different classes. The distance between the hyperplane and the nearest data points is called the margin, and the goal is to maximize the margin in order to make the model more robust and generalize better to new data.
In a regression task, an SVM algorithm will take a set of labeled training data and learn a model that can predict a continuous output value for new, unseen data. The model is again represented as a hyperplane in a high-dimensional space, and the goal is to find the hyperplane that best fits the data.
Support vector machines (SVMs) can be used in a variety of natural language processing (NLP) tasks, including dialog agents, natural language dialog systems, and natural language understanding (NLU) modules. Here are a few examples of how SVMs might be used in these contexts:
- Dialog agent: An SVM-based dialog agent might use SVMs to classify user inputs and identify the appropriate response. For example, the agent might use an SVM to classify a user’s input as a question, a request, or a statement, and then use this classification to decide how to respond. The agent might also use SVMs to classify the sentiment of the user’s input and adjust its tone or style of response accordingly.
- Natural language dialog system: An SVM-based natural language dialog system might use SVMs to classify and classify user inputs and generate appropriate responses. The system might also use SVMs to identify and classify named entities in the user’s input, such as people, organizations, and locations, and to extract relevant information from the input.
- Natural language understanding (NLU) module: An SVM-based NLU module might use SVMs to classify user inputs and identify the intent behind the input, such as booking a flight, ordering food, or making a reservation. The module might also use SVMs to classify the sentiment of the user’s input and extract other relevant information, such as dates, times, and locations.
In 2018, there was an explosion in the number of academic papers on SVM and chatbots.
Resources:
- tweetyproject.org .. java libraries for logical aspects of artificial intelligence and knowledge representation
Wikipedia:
See also:
100 Best Support Vector Machine Videos
Waiting for a sales renaissance in the fourth industrial revolution: Machine learning and artificial intelligence in sales research and practice
N Syam, A Sharma – Industrial Marketing Management, 2018 – Elsevier
… Fig. 1. Support Vector Machine … The third industrial revolution has already had a deep impact on this type of sale and, with the advent of machine learning and AI-powered chatbots, we expect the fourth industrial revolution to have maximal impact in these areas …
Wild patterns: Ten years after the rise of adversarial machine learning
B Biggio, F Roli – Pattern Recognition, 2018 – Elsevier
Skip to main content …
Extending a conventional chatbot knowledge base to external knowledge source and introducing user based sessions for diabetes education
S Hussain, G Athula – 2018 32nd International Conference on …, 2018 – ieeexplore.ieee.org
… later processing by a Responder [8]. In the published literature reviewed on chatbots, Lokman has … 13], which took two steps to classify the replies using ranking SVM (Support Vector Machine), and extracted <thread-title, reply> pairs automatically as chatbot knowledge …
How banks can better serve their customers through artificial techniques
A Vieira, A Sehgal – Digital Marketplaces Unleashed, 2018 – Springer
… In contrast, shallow models (two?layers neural network or support vector machine) present very few … forwardlook.com/indian-mobile-only-bank-handles-customer-service-with-chatbots/. 20 … do-your-banking-with-a-chatbot, Massachusetts: MIT Technology Review, 2016.Google …
Anomaly detection for short texts: Identifying whether your chatbot should switch from goal-oriented conversation to chit-chatting
A Bakarov, V Yadrintsev, I Sochenkov – International Conference on Digital …, 2018 – Springer
… agents are distinct by the purpose of their use: there are so-called general conversation agents, or chatbots which do … However, the main issue comes when one wants to extend the conversational agents to a chatbot, ie to implement both of … One-Class Support Vector Machine …
Moon IME: neural-based chinese pinyin aided input method with customizable association
Y Huang, Z Li, Z Zhang, H Zhao – Proceedings of ACL 2018, System …, 2018 – aclweb.org
… (Jiang et al., 2007) put forward a PTC framework based on support vector machine … 2017. Sequential matching network: A new architecture for multi-turn response selection in retrieval-based chatbots. In ACL, pages 496–505. Shaohua Yang, Hai Zhao, and Bao-liang Lu …
Argument harvesting using chatbots
LACFL HAMILTON, A Hunter… – Computational Models of …, 2018 – books.google.com
… We trained a Support Vector Machine with a linear kernel using the bag-of-words model … see Appendix C [1]. From the results, it can be concluded that a chatbot can indeed … LA Chalaguine et al./Argument Harvesting Using Chatbots 157 Table 4. Meaningful arguments (Args) in …
The Risk of Machine-Learning Bias (And How to Prevent It)
C DeBrusk – MIT Sloan Management Review, 2018 – oliverwyman.com
… In 2016, for example, an attempt by Microsoft to converse with millennials using a chat bot plugged into Twitter famously created a racist machine that switched from tweeting that “humans are super cool” to praising Hitler and spewing out misogynistic … Support vector machine …
Automated facilitation for idea platforms: design and evaluation of a Chatbot prototype
N Tavanapour, EAC Bittner – 2018 – aisel.aisnet.org
… The intents classification is realized with an SVM (Support Vector Machine) on training data also collected … skills (Clawson and Bostrom (1996)) for effective facilitation within the chatbots’ application … The first evaluation of our chatbot software prototype in UTs reveals the potential …
Deep learning for affective computing: Text-based emotion recognition in decision support
B Kratzwald, S Ili?, M Kraus, S Feuerriegel… – Decision Support …, 2018 – Elsevier
… Similarly, all systems with human-computer interactions (eg chatbots and personal assistants) could further benefit from emotion recognition … Consistent with these works, we later draw upon machine learning models (ie, random forest and support vector machine) together with tf …
Decision support with text-based emotion recognition: Deep learning for affective computing
B Kratzwald, S Ilic, M Kraus… – arXiv preprint arXiv …, 2018 – pdfs.semanticscholar.org
… [55] User interaction Chabots Regulation of emotion of stranded passengers through chatbots [56] … ing [72, 31]. Consistent with these works, we later draw upon machine learning models (ie random forest and support vector machine) together tf-idf features as our baseline …
Automatic processing and classification of citizens’ reports
G Angiani, P Fornacciari, G Lombardo… – Proceedings of the 4th …, 2018 – dl.acm.org
… KEYWORDS Text analysis, Image classification, Government 2.0, Chatbot … by government and administrations in the form of conversational chatbots (eg [7 … other well known automatic classification algorithms, namely: Random Forest (RF), Support Vector Machine (SVM), and K …
Artificial Intelligence Powered Banking Chatbot
KS Kumar, S Tamilselvan, BI Sha… – International …, 2018 – pdfs.semanticscholar.org
… best approach: According to scores of above table, 2 most correct algorithms are – Random Forest classifier and Support Vector Machine classifier … [13] https://apps.worldwritable.com/tutorials/chatbot … http://www.wildml.com/2016/04/deep- learning-for-chatbots- part -1-introduction …
Automated Scoring of Chatbot Responses in Conversational Dialogue
SK Yuwono, W Biao, LF D’Haro – pdfs.semanticscholar.org
… WOCHAT1, a workshop on chatbots and conversational agents releases a number of datasets … For each pair of human-chatbot turns, the bag-of-words repre- sentations are … Support vector machine (SVM) is a supervised learning model for classifica- tion, that performs well in …
LSTM Based Self-Defending AI Chatbot Providing Anti-Phishing
SS Kovalluri, A Ashok, H Singanamala – Proceedings of the First …, 2018 – dl.acm.org
… the category, each categorized email is transferred to dedicated chatbot rooms. Each category has specially trained chatbots, and they will reply back to the … Forest 95.414% Decision Tree 92.9798% Multi-Layer Perceptron 91.0454% Support Vector Machine 83.6557% Naïve …
A novel semantic matching method for chatbots based on convolutional neural network and attention mechanism
F Shan, L Zhao, Y Feng – Revue d’Intelligence Artificielle, 2018 – search.proquest.com
… The latest chatbots, which adopts deep learning techniques, can conduct colloquial conversations through autonomous … Semantic matching is the key to chatbot development … naive Bayes (Jiang et al., 2016), maximum entropy method and support vector machine (SVM) (Li and …
Chatbol, a chatbot for the Spanish “La Liga”
C Segura, A Palau, J Luque, M Costa-jussa, R Banchs – 2018 – oar.a-star.edu.sg
… During all these years, chatbots have been approached from different perspectives which … This sentence representation is used to train a multiclass support vector machine used to … We are also currently implementing interactive message buttons after each chatbot response to …
A Medical ChatBot
MR Dharwadkar, MNA Deshpande – ijcttjournal.org
… Patients who feel included, who are interacting through chatbots with the healthcare system, will stay … The Chatbot API sends query to chatbot and get related answer and refer this … A. Support Vector Machine Algorithm(SVM): SVM is a powerful classifier that is able to distinguish …
Focused domain contextual AI chatbot framework for resource poor languages
A Paul, A Haque Latif, F Amin Adnan… – Journal of Information …, 2018 – Taylor & Francis
… of our work is to avoid the incompetence of the existing chatbots and provide … The structure of the data set for training the chatbot was well thought so that … mining and machine learning techniques such as – Centroid, K nearest neighbour, Support Vector Machine, various Neural …
A Machine Learning Approach to Persian Text Readability Assessment Using a Crowdsourced Dataset
H Mohammadi, SH Khasteh – arXiv preprint arXiv:1810.06639, 2018 – arxiv.org
… In addition to a vast number of Telegram users in Iran, Telegram messenger is capable of hosting third- party chatbots … The processed features and the difficulty levels, derived from the chatbot are then fed to classifiers such as support vector machine, linear sup- port vector …
Education 4.0-Artificial Intelligence Assisted Higher Education: Early recognition System with Machine Learning to support Students’ Success
M Ciolacu, AF Tehrani, L Binder… – 2018 IEEE 24th …, 2018 – ieeexplore.ieee.org
… In this phase students are verifying their knowledge with Self-assessments questionnaires (quiz) also an intelligent Chatbot is available … this study is to reduce the failure rate in examinations by applying machine learning techniques such as Support Vector Machine (SVM) and …
Utterance Censorship of Online Reinforcement Learning Chatbot
Y Chai, G Liu – 2018 IEEE 30th International Conference on …, 2018 – ieeexplore.ieee.org
… The feedback immediately becomes the chatbot’s most likely prediction for that prompt … These recent chatbots [5] [6] also have the ability to learn from real users via reinforcement learning … Then, they input these features to a support vector machine (SVM) classifier …
Automatic Evaluation of Neural Personality-based Chatbots
Y Xing, R Fernández – arXiv preprint arXiv:1810.00472, 2018 – arxiv.org
… Evaluating the output of chatbot systems is re- markably difficult (Liu et al., 2016) … Since gen- eral responses are a known problem in neural re- sponse generation chatbots (Sordoni et al … We then use a support vector machine classifier7 to test to what extent the OCEAN scores …
Classifying Urgency: A Study in Machine Learning for Classifying the Level of Medical Emergency of an Animal’s Situation
D Strallhofer, J Ahlqvist – 2018 – diva-portal.org
… To counteract this the Linear Support Vector Machine is trained to only recognize words that have shown up at least 3 number of times in the dataset … The train sets are used to build a model using either Multinomial Naive Bayes or Linear Support Vector Machine …
Sentimental Analysis for AIML-Based E-Health Conversational Agents
D Ireland, H Hassanzadeh, SN Tran – International Conference on Neural …, 2018 – Springer
… Sentiment analysis E-health chatbots. Download conference paper PDF … dictionary using a directed graph model while the others are the well-known Naive Bayes classifier, support vector machine (SVM), convolutional … 1. Overview of the chatbot system showing the three stages …
Smart Complaint Management System
P Kormpho, P Liawsomboon… – 2018 Seventh ICT …, 2018 – ieeexplore.ieee.org
… For the SMO, it is an algorithm for solving the Support Vector Machine (SVM) quadratic programming (QP … 19 shows the satisfaction level of using our mobile application and chatbot, all of the … Available from: https://venturebeat.com/2016/08/26/3-stats- that-show-chatbots-are-here …
Comparing the Effectiveness of Support Vector Machines and Convolutional Neural Networks for Determining User Intent in Conversational Agents
KO Sullivan – 2018 – arrow.dit.ie
… List of Acronyms SVM Support Vector Machine NB Naive Bayes CNN Convolutional Neural Net- work … Conversational agents are computer systems which communicate with users employing natural language and fall into two broad categories; chatbots and task-oriented agents …
Understanding the Adoption of Chatbot
HN Io, CB Lee – Future of Information and Communication Conference, 2018 – Springer
… based techniques can be supervised or unsupervised, some popular methods include: Naïve Bayes, Support Vector Machine, k-Nearest … Mining the data about what Siri users think about the chatbot is useful as it can determine how or why people really use chatbots …
Pre-Consulting Dialogue Systems for Telemedicine: Yes/No Intent Classification
T Mairittha, T Okita, S Inoue – Proceedings of the 2018 ACM International …, 2018 – dl.acm.org
… Further, it turned out that useful kinds of questions in chatbot at this stage are related to Yes/No questions … A Logistic Re- gression, Naive Bayes, and Support Vector Machine (SVM), and Xtereme Gradient Boosting (XGBoost) were also tried with Count Vectors as features …
Argumentation system for intelligent assistants using fuzzy-based reasoning
T Koivuaho, M Ibrahim, F Ummul, M Oussalah – World Scientific
… infancy, and more research is still needed in order to open new horizons for chatbots … rule based system in order to yield the prototype of potential chatbot answer … topics (gathered using Drichlet latent modelling), dialogue act (using corpus and support vector machine), five-trait …
Argument Harvesting Using Chatbots
AC Lisa, FL HAMILTON, A HUNTER, HWW POTTS – comma2018.argdiap.pl
… We trained a Support Vector Machine with a linear kernel using the bag-of-words model … Our future aim is to develop a chatbot for persuading people to change their behaviour or belief by answering with suitable counterarguments … [3] How chatbots sill shape the future of …
Sentiment Analysis on Online Product Reviews
R Bose, RK Dey, S Roy, D Sarddar – researchgate.net
… technique to analyze and comprehend large amounts of customers’ opinions where different companies build a chatbots to support … In [16], authors shown that Support vector machine (SVM) perform better accuracy compared to Naïve bayes and maximum entropy methods …
XiaoA: A Robot Editor for Popularity Prediction of Online News Based on Ensemble Learning
F Long, M Xu, Y Li, Z Wu, Q Ling – International Conference on Intelligence …, 2018 – Springer
… It is a chat bot within the messaging app Slack, which utilizes machine learning in its backend … Several classifiers are chosen as our component learners such as Random forest (RF), Neural network (NN), Support vector machine (SVM), Logistic regression (LR), Nearest centroid …
Between the Lines: Machine Learning for Prediction of Psychological Traits-A Survey
D Johannßen, C Biemann – … Domain Conference for Machine Learning and …, 2018 – Springer
… [12]. The dataset originated from a clinical study at the MIT and can be implemented as chatbot service … Shen et al. [13] detected anxiety on Reddit by using depression lexicons for their research and training Support Vector Machine (SVM, Cortes et al …
Advances in Computational Intelligence Systems
A Lotfi, H Bouchachia, A Gegov, C Langensiepen… – Intelligence, 2018 – Springer
… and Amar Aggoun Learning from Interaction: An Intelligent Networked-Based Human-Bot and Bot-Bot Chatbot System … Iwata, Kazuya Odagiri, and Toyoshiro Nakashima Anomaly Detection in Activities of Daily Living Using One-Class Support Vector Machine …
Digitalization & Big Data
J Zolkiewski, V Story, J Burton, P Chan… – Computers in Human … – bwl.uni-mannheim.de
… of this work is to give an overview of the extent to which companies imbue chatbots with human … Araujo, Theo (2018), “Living up to the chatbot hype … Cui, Dapeng and David Curry (2005), “Prediction in Marketing Using the Support Vector Machine,” Marketing Science, 24 (4), 595 …
Robust Approach to Detection of Bubbles Based on Images Analysis
HT Nguyen, LT Nguyen, AI Dreglea – 2018 – researchgate.net
… Softw. Eng. 1: 799–801. Xuewen, M., Xiaoping, S. and Kirby, J. 2017. Support vector machine classifier based on approximate entropy metric for chatbot text-based communication, International Journal of Artificial Intelligence 15: 1–16. Yujin, Z., LiMing, B. and Wang, S. 2006 …
Bangla Interrogative Sentence Identification from Transliterated Bangla Sentences
MM Hamid, T Alam, S Ismail… – … Conference on Bangla …, 2018 – ieeexplore.ieee.org
… For employing supervised learning, we use machine learning techniques such as Support Vector Machine, k-Nearest Neighbors, Multilayer … smart assist applications, medical applications, question-answering based applications, user-interactive applications, chatbot pro- grams …
Classification algorithms in Data Mining
SS Alaoui, Y Farhaoui, B Aksasse – researchgate.net
… Rev. Data Min. Knowl. Discov. 1, 431–443. https://doi.org/10.1002/widm.24 Mu, X., Shen, X., Kirby, J., 2017. Support Vector Machine Classifier Based on Approximate Entropy Metric for Chatbot Text-based Communication. Int. J. Artif. Intell. 15, 1–16. Provost, F., Kohavi, R., 1998 …
Priority Based Sentiment Analysis for Quick Response to Citizen Complaints
KV Deshmukh, SS Shiravale – 2018 3rd International …, 2018 – ieeexplore.ieee.org
… Support Vector Machine Classifier (SVM): This method is used to categorize the search space linearly for the separation of two dissimilar … 1–6 ,2013 [25] S reshmi and Kannan Balakrishnan, “Implementation of an inquisitive chatbot for database supported knowledge bases …
Multimodal cognitive processing using artificial endocrine system for development of affective virtual agents
H Samani – ????? ???????, 2018 – mathnet.ru
… In this work, we used support vector machine since the training of the system is simple and has no extra complexity based on local minimas … pp. 412–415. 4. Benton M. et al. Quality in Chatbots and Intelligent Conversational Agents … 49. Alfonsi B. “Sassy” Chatbot Wins with Wit …
Vietnamese Diacritics Restoration Using Deep Learning Approach
BT Hung – 2018 10th International Conference on Knowledge …, 2018 – ieeexplore.ieee.org
… pointwise approach for recovering missing diacritics automatically; this approach applies three characteristics of Support Vector Machine model for … written Vietnamese texts is important for many applications including question-answering, text extraction, chatbot, search engines …
A Trustworthy, Responsible and Interpretable System to Handle Chit-Chat in Conversational Bots
P Agrawal, A Suri, T Menon – arXiv preprint arXiv:1811.07600, 2018 – arxiv.org
… a good amount of distinct queries made to a popular personal- assistant chat-bot … in Figure 2, we trained an ensemble of models, where a Support Vector Machine (SVM) (Cortes … Docchat: An information re- trieval approach for chatbot engines using unstructured doc- uments …
An Efficient Real Time Model For Credit Card Fraud Detection Based On Deep Learning
Y Abakarim, M Lahby, A Attioui – … of the 12th International Conference on …, 2018 – dl.acm.org
… In the financial landscape, for example, Machine Learning is used to build Chatbots, an artificial intelligence software that can interact with the customers and respond to there queries … 0 or 1 Table 3: Comparison Algorithms Support Vector Machine Linear SVM Regression …
Systematic Literature Review on Customer Emotions in Social Media
P Madhala, J Jussila, H Aramo-Immonen… – ECSM 2018 5th …, 2018 – books.google.com
… companion on World Wide Web 21 (Xu et al., 2017) A New Chatbot for Customer … Bayes Proposed algorithm accuracy for sentiment Sometimes, tweets contain no (NB), Support vector machine (SVM), C4 … Xu et al.(2017) applied emotion detection in customer service chatbots …
Metis: A Scalable Natural-Language-Based Intelligent Personal Assistant for Maritime Services
N Gkanatsios, K Mermikli, S Katsikas – International Conference on …, 2018 – Springer
… Strong classifiers (Support Vector Machine and Random Forest classifier) are trained to generalize well … BA, Atwell, E.: Different measurements metrics to evaluate a chatbot system … Radziwill, NM, Benton, MC: Evaluating quality of chatbots and intelligent conversational agents …
A Study on Dialogue Reward Prediction for Open-Ended Conversational Agents
H Cuayáhuitl, S Ryu, D Lee, J Kim – arXiv preprint arXiv:1812.00350, 2018 – arxiv.org
… which can be used to optimise the behaviour of dialogue agents such as chit-chat chatbots … 17, 8, 7]. [17] train a neural multiclass classifier and linear regressor from human-chatbot dialogues from … [20] Bus, Restaurants, Hotels, Laptops Support Vector Machine (SVM) Walker et …
Text mining analysis of teaching evaluation questionnaires for the selection of outstanding teaching faculty members
CW Tseng, JJ Chou, YC Tsai – IEEE Access, 2018 – ieeexplore.ieee.org
… 9 Inverse Document Frequency (TF-IDF) method, classification is conducted using Support Vector Machine (SVM) and fully connected neural network … Attention RNN: The attention mechanism is currently a very popular technology used in chatbots and machine translation …
A 20% Jump in Duplicate Question Detection Accuracy? Replicating IBM team’s experiment and finding problems in its data preparation
J Silva, J Rodrigues, V Maraev, C Saedi, A Branco – META, 2018 – lrec-conf.org
… Both tasks have been useful to support conversational interfaces and chat- bots, in general, and online question & answering (Q&A … overlap with shingling (n-grams) and a Jaccard coefficient; (ii) a standard machine learn- ing method, namely Support Vector Machine (SVM); and …
Demoing platypus–A multilingual question answering platform for wikidata
TP Tanon, MD de Assuncao, E Caron… – European Semantic Web …, 2018 – Springer
… the question by the average of the word embeddings of its words, and classify them with a linear support vector machine … 2017)Google Scholar. 4. Athreya, RG, Ngomo, ACN, Usbeck, R.: Enhancing community interactions with data-driven chatbots – the DBpedia chatbot …
Automated emergency paramedical response system
M Srivastava, S Suvarna, A Srivastava… – … information science and …, 2018 – Springer
… Overview of the working of the chatbot … 5. Support vector machine Support Vector machine finds an optimal hyperplane that separates the maximum number of points belonging to the same class on the same side of the hyperplane along with keeping the maximum distance from …
Artificial Intelligence for Conversational Robo-Advisor
MY Day, JT Lin, YC Chen – 2018 IEEE/ACM International …, 2018 – ieeexplore.ieee.org
… This type of chatbots is more suitable for the knowledge base and retrieval-based models … Section 2 describes the literature on asset allocation, DL, and chatbot … Several of the well-developed ML models, such as support vector machine, which have high stability, have …
Artificial Intelligence Architecture Inspired by Personality Theory
GA Popoola, CA Graves – 2018 IEEE International Symposium …, 2018 – ieeexplore.ieee.org
… Unlike chatbots that are built specifically for conversation, strong AI systems are built to have the same sensory perception as a human and … These four classic classifiers are: (1) a decision tree (DT), (2) a multilayer perceptron (MLP), (3) a support vector machine (SVM), and (4) a …
Artificial Intelligence in Disaster Risk Communication: A Systematic Literature Review
RI Ogie, JC Rho, RJ Clarke – 2018 5th International …, 2018 – ieeexplore.ieee.org
… The use of chat bots and other forms of AI-based communication systems can … Forest, Support Vector Machine (SVM), and Naïve Bayes in achieving the extraction of informative social … to provide personalized service is grossly inadequate, AI powered chatbots can potentially …
Intelligent Autonomous Systems for Software Engineering-An Example
RT Prasad, G Pallail, JJ Mukkada – … International Conference on …, 2018 – ieeexplore.ieee.org
… According to category assigned, a chat bot assisted queries/and auto recording of user responses are offered to service desk … Support Vector Machine (SVM) will help classify the tickets based on the nature as detailed in the incident description …
Role of data properties on sentiment analysis of texts via convolutions
E Çano, M Morisio – World Conference on Information Systems and …, 2018 – Springer
… Self-driving cars, intelligent personal assistants and chat bots passing Turing test, are some examples of today’s deep learning revolution … BOW and tf-idf have proved to be very effective on several text classification tasks, especially when support vector machine is used as …
Lawyer’s Intellectual Tool for Analysis of Legal Documents in Russian
A Khasianov, I Alimova, A Marchenko… – … and Innovations (IC …, 2018 – ieeexplore.ieee.org
… was built in accordance with the architecture of three-agent intelligent systems [1], [2]. The intelligent agent has several interfaces: a messenger-based chatbot, a mobile … The proposed approach was compared with a model based on support vector machine and outperformed it …
Deep Highway Networks and Tree-Based Ensemble for Predicting Short-Term Building Energy Consumption
M Ahmad, A Mouraud, Y Rezgui, M Mourshed – Energies, 2018 – mdpi.com
… However, these techniques have been extensively applied in the vision domain; various other research works have also applied deep-learning methods for other research areas, eg, cancer (diagnosis and detection) [19], chatbots and NLP (Natural Language Processing) [20 …
A Joint Model based on CNN-LSTMs in Dialogue Understanding
X Zhao, E Haihong, M Song – 2018 International Conference on …, 2018 – ieeexplore.ieee.org
… I. INTRODUCTION With the rise of artificial intelligence wave, chat-bot has become one of the most popular research directions … been used to solve text classification problems, such as K-Nearest Neighbors (KNN) [2], Naive Bayes (NB) [3], and Support Vector Machine (SVM) [4 …
ProMETheus: An Intelligent Mobile Voice Meeting Minutes System
H Liu, X Wang, Y Wei, W Shao, J Liono… – Proceedings of the 15th …, 2018 – dl.acm.org
… ˆui = am i Ei (x) + (1 ? a m i )ui am i = ni ni + rm (3) 4.2.2 Support Vector Machine … The set of architecture is known as seq2seq [23] and is widely used in the scenarios where there are input sequences and output sequences, such as machine translations, and chat bots …
Natural Language Semantic Construction Based on Cloud Database
S Wang, L Zhang, Y Zhang, J Sun… – CMC-COMPUTERS …, 2018 – tsp.techscience.com
… The literature [Zhao, Li and Jiang (2016)] discloses a method for natural language understanding of intention, using intentions tagging, text vectoring and support vector machine to understand natural language instruction. He et al. [He, Deng, Gao et al …
Task graph based task-oriented dialogue system using dialogue map for second language learning
OW Kwon, YK Kim, Y Lee – Future-proof CALL: language …, 2018 – books.google.com
… dialogue system suitable for CALL can be viewed as a Task-oriented Dialogue System (TDS) rather than a chatbot system, as … Our TDS consists of a Structured Support Vector Machine (SSVM) based NLU (Kwon, Lee, Kim, & Lee, 2015), task graph-based dialogue management …
An AWS Machine Learning-Based Indirect Monitoring Method for Deburring in Aerospace Industries Towards Industry 4.0
W Caesarendra, B Pappachan, T Wijaya, D Lee… – Applied Sciences, 2018 – mdpi.com
… The machine learning application service consists of APIs for vision services, language services, and chatbots. Some use cases include face recognition services, speed recognition, speech-to-text translations, and the building of interactive chatbots …
Finbrain: When finance meets ai 2.0
X Zheng, M Zhu, Q Li, C Chen, Y Tan – arXiv preprint arXiv:1808.08497, 2018 – arxiv.org
… 2016), and support vector machine model (Han, Han et al … Recent developments on speech recognition and natural language processing enable machine-to-hu- man communication via interactive smart Q&A inter- faces (eg, chatbot systems such as Siri and Cortana) (Etzioni …
Efficient repair of polluted machine learning systems via causal unlearning
Y Cao, AF Yu, A Aday, E Stahl, J Merwine… – Proceedings of the 2018 …, 2018 – dl.acm.org
… The most recent real-world example is Microsoft’s AI powered chatbot Tay. Tay learned racism because some Twit- ter users interacted with Tay using offensive, racist words, and these words were included in Tay’s training set [36] …
A Neural Architecture for Multi-label Text Classification
S Coope, Y Bachrach, A Žukov-Gregori?… – Proceedings of SAI …, 2018 – Springer
… and prediction [16, 17] question-answering [18], named-entity recognition [19] and chatbots [20, 21]. 4 … Scholar. 3. Zhang, K., Xu, H., Tang, J., Li, J.: Keyword extraction using support vector machine … T., Pieper, M., Chandar, S., Ke, NR, et al.: A deep reinforcement learning chatbot …
Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications
CR Rao, VN Gudivada – 2018 – books.google.com
… Classification Algorithms 6.1 Decision Tree Algorithm 6.2 Naive Bayesian Classification 6.3 Support Vector Machine Clustering Algorithms 7.1 k … generation, semantic analysis, grammar correction, question- answering systems, spoken dialog systems, chatbots, passage retrieval …
Emotional dialogue generation using image-grounded language models
B Huber, D McDuff, C Brockett, M Galley… – Proceedings of the 2018 …, 2018 – dl.acm.org
… eg, to the common set of six “basic” emotions.) We used facial coding software to extract the facial actions of the faces within the images [3]. The classifier extracts appearance-based information from the face region- of-interest and a Support Vector Machine (SVM) classifier …
Artificial Intelligence By Example: Develop machine intelligence from scratch using real artificial intelligence use cases
D Rothman – 2018 – books.google.com
… a parking space Deciding how to get to the parking lot Support vector machine The itinerary … Table of Contents Chapter 15: Cognitive NLP Chatbots Technical requirements IBM Watson Intents Testing … Scripting and building up the model Adding services to a chatbot A cognitive …
Machine learning for software analysis: Models, methods, and applications
A Bennaceur, K Meinke – … for Dynamic Software Analysis: Potentials and …, 2018 – Springer
Machine Learning (ML) is the discipline that studies methods for automatically inferring models from data. Machine learning has been successfully applied in many areas of software engineering…
Machine Learning in Official Statistics
M Beck, F Dumpert, J Feuerhake – arXiv preprint arXiv:1812.10422, 2018 – arxiv.org
… Status: Status of the project – Productive – Experiment – Test – Idea Method: Which machine learning method was used, eg: – Support vector machine (SVM) – Decision trees – Random forest – Neural networks Software: Which software is used (eg R, Python, etc.) …
Cognitive Internet of Things (IoT) in Medical Analytics
H Bedekar – 2018 – search.proquest.com
… the key for the reduction of multiple classification issues in a vast class of application fields [4], and the supervised support vector machine (SVM) has been used extensively in data classification problems [5] … The other application is called Chatbots, a designed computer …
Emotion detection from text and speech: a survey
K Sailunaz, M Dhaliwal, J Rokne, R Alhajj – Social Network Analysis and …, 2018 – Springer
… any national, international or political event, detecting potential criminals or terrorists from analyzing the emotions of people after a terrorist attack or crime, improving the performances of chatbots and other … Naive Bayes, support vector machine, decision tree, K-nearest Neighbor …
Developing Disease Classification System based on Keyword Extraction and Supervised Learning
M Suffian, MY Khan, S Wasi – INTERNATIONAL JOURNAL OF …, 2018 – researchgate.net
… (b) Iterative Dichotomiser 3 (ID3) [18] which is the classifying algorithm that works as a decision tree, (c) Support vector machine (SVM) [19] which is the linear model of classification where data is split into distinct parts in such a way that it holds maximum margin among the splits …
Inferring User Emotive State Changes in Realistic Human-Computer Conversational Dialogs
R Li, Z Wu, J Jia, J Li, W Chen, H Meng – 2018 ACM Multimedia …, 2018 – dl.acm.org
… chenweibj8871@sogou-inc.com Helen Meng The Chinese University of Hong Kong hmmeng@se.cuhk.edu.hk ABSTRACT Human-computer conversational interactions are increasingly per- vasive in real-world applications, such as chatbots and virtual assis- tants …
Explicit Interaction Model towards Text Classification
C Du, Z Chin, F Feng, L Zhu, T Gan, L Nie – arXiv preprint arXiv …, 2018 – arxiv.org
… models such as Linear Regression (Zhu and Hastie 2001) and Support Vector Machine (Cortes and Vapnik 1995) to make the judgment … source and target textual contents, such as natural language inference (Wang and Jiang 2016b) and retrieve-based chat- bot (Wu et al …
Analyzing and Predicting Emoji Usages in Social Media
P Zhao, J Jia, Y An, J Liang, L Xie, J Luo – Companion of the The Web …, 2018 – dl.acm.org
… our model. We se- lect five methods as follows: Random selection, Logistic Regression (LR), Support Vector Machine (SVM), Deep Neural Network (DNN), Gated Recurrent Unit (GRU) and the proposed model. • Random. We …
Engineering doc2vec for automatic classification of product descriptions on O2O applications
H Lee, Y Yoon – Electronic Commerce Research, 2018 – Springer
… receipt of the product inquiry from the online buyers, the chatbot automatically retrieves … Instead we can have chatbots respond to the requests for product registrations and … accuracy using the following three algorithms: Naïve Bayes, SVM (Support Vector Machine) and KNN (K …
Automatic generation of comments on twitter based on news
C Casar Morejon – 2018 – upcommons.upc.edu
… 30 4.8.1 Support Vector Machine (SVM) … These chatbots are widely known, and almost every company has one, like Alexa from amazon to google Allo … Also, we did have put some extra hours to learn some deep learning and how chatbot works in order to make a good comment …
Detecting Malicious Windows Commands Using Natural Language Processing Techniques
MM Yamin, B Katt – International Conference on Security for Information …, 2018 – Springer
… scenario of obfuscated malicious VBA macros detection [4] used five different classifiers SVM (Support Vector Machine), RF (Random Forest … We used natural language processing techniques developed for chat bots sentence classification to classify malicious obfuscated CMD …
Sentiment Analysis with Core ML
M Mitrevski – Developing Conversational Interfaces for iOS, 2018 – Springer
… In conversational interfaces, sentiment analysis is perfect for developing chatbots, which based on a user’s sentiment can do different actions … The resulting model is Linear Support Vector Machine (LinearSVM), which is trained with a TF-IDF vectorized dataset …
“I think it might help if we multiply, and not add”: Detecting Indirectness in Conversation
P Goel, Y Matsuyama, M Madaio, J Cassell – articulab.hcii.cs.cmu.edu
… For each feature representation, we tried the following supervised machine learning algorithms – Logistic Regression, Naive Bayes, Random Forest and Support Vector Machine (SVM), with Logistic Reg … Reynolds, M.: Chatbots learn how to drive a hard bargain (2017) 38 …
Recurrent convolutional neural network for answer selection in community question answering
X Zhou, B Hu, Q Chen, X Wang – Neurocomputing, 2018 – Elsevier
… for generating useful question–answer (QA) pairs, which are valuable to enrich the knowledge base of many intelligent systems, like automatic question answering [1] or chatbot [2]. Even … 2] extracted QA pairs from the forum threads by using Support Vector Machine (SVM) model …
Deep learning for detecting inappropriate content in text
H Yenala, A Jhanwar, MK Chinnakotla… – International Journal of …, 2018 – Springer
… For our current work, we collected real-world conversational data from gaming application and chat bots … compare our approach with three baselines—(a) Pattern and Keyword-based Filtering (PKF) and (b) Support Vector Machine (SVM) [6 … Zo Conversation (Zo is a chat bot.) 3 …
Inter-Category Distribution Enhanced Feature Extraction for Efficient Text Classification
Y Wang, J Huang, Y Liu, L Tu, L Liu – International Conference on Big …, 2018 – Springer
… have been applied successfully in many big data driven text applications and services, such as spam filtering [2], tagging online news [3], social media analysis [4], bioscience [5] and chat bot [6]. Statistical learning based methods, such as Support Vector Machine (SVM) and its …
Introduction to the Thematic Section on Computational Linguistics
A Gelbukh – Computación y Sistemas, 2018 – cys.cic.ipn.mx
… In particular, they compare how alternative encoder- decoder deep learning architectures perform in the context of chatbots … A Support Vector Machine was trained, and he found that attachment style could be predicted from text within a range of 64% to 85% for different …
Artificial intelligence (AI) methods in optical networks: A comprehensive survey
J Mata, I De Miguel, RJ Duran, N Merayo… – Optical switching and …, 2018 – Elsevier
Skip to main content …
A review on data fusion methods in multimodal human computer dialog
M YANG, J TAO – vr-ih.com
… In addition to the above multi-channel information fusion calculation model, there are many other models also used for multi-channel information fusion, such as multi-level support vector machine, decision regression tree, random forest and other methods, because the length …
Deep Learning: Future Of Artificial Intelligence
S SHARMA – Global Journal on Innovation …, 2018 – technology.eurekajournals.com
… Support Vector Machine • Serial Invariant Feature Transform • Boost Up Robust Features • Median Binary Pattern(LBP) • Feature from Accelerated Segment Test(FAST) … Many devices uses Google assistants services, chat bot services etc …
Advanced Data Analytics Using Python: With Machine Learning, Deep Learning and NLP Examples
S Mukhopadhyay – 2018 – books.google.com
… TABLE OF CONTENTS TABLE OF CONTENTS Naive Bayes Classifier…..61 Support Vector Machine…..62 Nearest Neighbor Classifier…..64 …
Artificial intelligence and machine learning: current applications in real estate
JJE Conway – 2018 – dspace.mit.edu
… Natural language generation give computers to ability to communicate back to us in “human” terms. These tools are used in real estate related chat bots, contract review and data extraction, data gathering and processing from text based sources, and document writing …
Improving response accuracy for classification-based conversational IT services
Y Diao, D Rosu – NOMS 2018-2018 IEEE/IFIP Network …, 2018 – ieeexplore.ieee.org
… use Watson Natural Language Classifier (NLC) based on the IBM Bluemix platform [2]. In order to make sure our evaluation is not biased by any particular classifier, we also consider two other classification methods: Na?ve Bayes [3] and Linear Support Vector Machine (SVM) [4 …
Artificial Intelligence and Machine Learning Fundamentals: Develop real-world applications powered by the latest AI advances
Z Nagy – 2018 – books.google.com
… 162 Parameters of the scikit-learn SVM ….. 163 Activity 9: Support Vector Machine Optimization in scikit-learn … Similarly, when we interact with a chatbot, we expect the botto understand us …
Mining Intellectual History Using Unstructured Data Analytics to Classify Thoughts for Digital Humanities
H Seo, O Kwon – ??????, 2018 – dbpia.co.kr
… This work was supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIP) (No.2017-0-01122, Development of personal profiling and personalized chatbot technology based on language usage pattern …
Business models based on IoT, AI and blockchain
J Liu – 2018 – diva-portal.org
… From the company side, they retrieve big data from the customers to foresee the market trend. Chatbots also have a great potential in the health industry … support vector machine. We target to provide a structural overview of these two models along …
Voice recognition by Google Home and Raspberry Pi for smart socket control
CY Peng, RC Chen – 2018 Tenth International Conference on …, 2018 – ieeexplore.ieee.org
… used Bluetooth to connect the coordinates and through three different machine learning methods (K-meanings analysis, support vector machine analysis, and … This paper investigates the establishment of an open domain chatbot database through the services provided by API.ai …
Cyber Security and Compliance Management through a Single Integrated Platform
MBAIMBAI MBA-ITBM – researchgate.net
… We have used a machine learning algorithm – Support Vector Machine for detecting phishing URL using different features of the link … In the platform we have provided a chat-bot for the employees which is linked to the security team of the organization …
Intelligent Interactive Multimedia Systems and Services: Proceedings of 2018 Conference
GD Pietro, L Gallo, RJ Howlett, LC Jain, L Vlacic – 2018 – dl.acm.org
Help Design Your New ACM Digital Library. We’re upgrading the ACM DL, and would like your input. Please sign up to review new features, functionality and page designs. Leave an email address: or Follow @ACMDL. or [Not interested]. Google, Inc. (search) …
Human Systems Engineering and Design: Proceedings of the 1st International Conference on Human Systems Engineering and Design (IHSED2018): Future …
T Ahram, W Karwowski, R Taiar – 2018 – books.google.com
… x Contents Putting Chatbots to the Test: Does the User Experience Score Higher with Chatbots Than Websites … Vasco Saavedra, Beatriz Sousa Santos, and Carlos Ferreira A Classification of Motor Imagery Brain Signals Using Least Square Support Vector Machine and Chaotic …
Open-domain neural conversational agents: The step towards artificial general intelligence
S Arsovski, S Wong, AD Cheok – International Journal of …, 2018 – openaccess.city.ac.uk
… After almost 50 years since the introduction of chatbots and numerous surveys over the … by applying deep reinforcement learning to model future reward in chatbot dialogue … an accuracy of 96%, a significantly higher accuracy compared to bigram support vector machine (SVM) [24 …
Artificial Intelligence in Smart Tourism: A Conceptual Framework
RH Tsaih, CC Hsu – Artificial Intelligence, 2018 – aisel.aisnet.org
… 5. Support vector machine. 6. Decision tree … The available product in market such as Chatbot, voice customer assistant, Starbucks in 2016 began using AI for serving personalization recommendation, Lowe’s bringing AI to three-dimensional space with LoweBots …
Inferring Human Traits from Facebook Statuses
A Cutler, B Kulis – International Conference on Social Informatics, 2018 – Springer
… For example, social media can be used to establish creditworthiness [2, 3], persuade voters [4, 5], or seek cognitive behavioral therapy from a chatbot [6]. Many of these tasks depend on knowing something about the personal life of the user …
Deep Neural Language Generation with Emotional Intelligence and External Feedback
V Srinivasan – 2018 – search.proquest.com
… Seq2Seq Sequence-to-Sequence SVM Support Vector Machine Page 12 … Next, the chatbot uses that information to come up with a relevant answer that is also emotionally appropriate. As the chatbots become emotionally in tune, people could have more fun chatting with them …
Dialogue scenario collection of persuasive dialogue with emotional expressions via crowdsourcing
K Yoshino, Y Ishikawa, M Mizukami, Y Suzuki… – Proceedings of the …, 2018 – aclweb.org
… SVR is an expansion of Support Vector Machine (SVM) for the re- Table 5: Example of annotated corpus Speaker Utterance Accept Emotion Sys Let’s clean the room — Neutral User No, it’s a bother … Chatbot evaluation and database expansion via crowd- sourcing …
Other Applications
A Vieira, B Ribeiro – Introduction to Deep Learning Business Applications …, 2018 – Springer
… machine learning methods in a variety of malicious code detection applications, including Naïve Bayes, decision trees, artificial neural networks, support vector machine, and so … Despite all the buzz around chatbots, they definitely will change the way users interact with content …
Identifying opinion and fact subcategories from the social Web
A Mullick, S Ghosh D, S Maheswari, S Sahoo… – Proceedings of the …, 2018 – dl.acm.org
… To design intelligent chat-bot system, categorical classifications are important because it may help to iden- tify mentalities of the … these balanced datasets, various classi- fiers from Weka [4] – Naïve Bayes (NB), Logistic Regression (LR), Support Vector Machine (SVM), Repeated …
Human Capacity—Biopsychosocial Perspective
B Xing, T Marwala – Smart Maintenance for Human–Robot Interaction, 2018 – Springer
… on allowing humans to easily and naturally communicate with other non-human entities (Raman & Sharma, 2015), say, the trendy chatbot … In the literature, plenty of predicting methods have been developed, such as support vector machine (Sapankevych & Sankar, 2009) …
Fact or Fiction
A Lu, CJ Lovering, N Dinh, C Tri, T Nguyen, H Bui – 2018 – digitalcommons.wpi.edu
… SVM Support Vector Machine … LUIS can also be used to get sentiment scores on entities, provide a framework to build chatbots upon, and is multilingual. Any client application that converses with users, such as a dialog system or a chatbot, can pass user input to a LUIS app and …
Mathematical Foundations Of Machine Learning
H VÂN LÊ – 2018 – users.math.cas.cz
… 3. Fisher metric and stochastic gradient descend. 4. Support vector machine, Kernel machine and Neural network. Recommended Literature … Most of those gamers will be humans; one will be a chatbot with the purpose of tricking the judge into thinking that it is the real human …
Measuring and comparing service quality metrics through social media analytics: a case study
W He, X Tian, A Hung, V Akula, W Zhang – Information Systems and e …, 2018 – Springer
… These sentiment analysis tools mainly rely on machine learning techniques such as Support Vector Machine (SVM), Naive Bayes, Maximum Entropy, and Matrix Factorization to classify … Therefore, our research can serve as the fundamentals of the chatbot’s brain development …
Software Architectures for Human-Machine Interaction Using Natural Language
G Tirone, CHMOPE ARDIZZONE, CHMOPA CHELLA… – 2018 – iris.unipa.it
Page 1. DIPARTIMENTO DELL’ INNOVAZIONE INDUSTRIALE E DIGITALE INGEGNERIA CHIMICA, GESTIONALE, INFORMATICA, MECCANICA Dottorato in Ingegneria dell’Innovazione Tecnologica – Ingegneria Informatica …
Neural networks for sentiment analysis in AsterixDB
JMK Finckenhagen – 2018 – brage.bibsys.no
… Node Controller NLP = Natural Language Processing RNN = Recurrent Neural Network SST = Stanford Sentiment Treebank SVM = Support Vector Machine TPS = Tweets Per … Self-driving cars, intelligent personal assistants like Siri and Alexa and chatbots are all over the news …
Deep Learning for Digital Text Analytics: Sentiment Analysis
M Kale, P Mankame, G Kulkarni – arXiv preprint arXiv:1804.03673, 2018 – arxiv.org
… by statistical Machine Learning approach that have used Document Term Matrix (representation) and Support Vector Machine (classification) … for legal phrase extraction [5], paraphrase detec- tion, sentiment analysis, question-answering – chat bots, document summarization …
Practical Java Machine Learning
M Wickham – Springer
… 197 K-Nearest Neighbors Algorithm (KNN) …. 199 Support Vector Machine Algorithm (SVM) …. 202 … 281 Classification: Support Vector Machine ….. 283 …
Practical Java Machine Learning: Projects with Google Cloud Platform and Amazon Web Services
M Wickham – 2018 – books.google.com
… 197 K-Nearest Neighbors Algorithm (KNN)…. 199 Support Vector Machine Algorithm (SVM) … 281 Classification: Support Vector Machine …
Implementation of A Neural Natural Language Understanding Component for Arabic Dialogue Systems
AM Bashir, A Hassan, B Rosman, D Duma… – Procedia computer …, 2018 – Elsevier
… Language) to implement a chatbot which was based on the Egyptian Arabic dialect. Elmadani et al. [13] demonstrated a similar approach to the one proposed in this paper by presenting an effective dialogue actions classification model using a Support Vector Machine (SVM) as …
Toward An Arabic Question Answering System Over Linked Data
A Bouziane, D Bouchiha, N Doumi… – Jordanian Journal of …, 2018 – researchgate.net
… It uses supervised support vector machine (SVM) classifier for question classification and answer selection, to generate the exact answer for a given question … In [42], the author describes a way to access Arabic Web Question Answering (QA) corpus using a chatbot (ALICE open …
Intelligent Data Engineering and Automated Learning–IDEAL 2018: 19th International Conference, Madrid, Spain, November 21–23, 2018, Proceedings
H Yin, D Camacho, P Novais, AJ Tallón-Ballesteros – 2018 – books.google.com
… 1 Figlu Mohanty, Suvendu Rup, and Bodhisattva Dash Support Vector Machine Based Method for High Impedance Fault Diagnosis in Power … 364 Alejandro Baldominos, Yago Saez, and Pedro Isasi Chatbot Theory: A Naïve and Elementary Theory for Dialogue Management …
Noise induced hearing loss: Building an application using the angelic methodology
L Al-Abdulkarim, K Atkinson… – Argument & …, 2018 – content.iospress.com
… extraction of rules is attempted in [6], but they do offer “the 20 most frequent words, listed in order of their SVM [Support Vector Machine] weight … The need to look critically at the training data is shown by Microsoft AI chatbot, Tay, a machine learning project,19 designed for human …
An empirical study on fine-grained named entity recognition
K Mai, TH Pham, MT Nguyen, NT Duc… – Proceedings of the 27th …, 2018 – aclweb.org
… Similarly, a chatbot software might require not only the recognition of Organization, but also the fine-grained classification to recognize a music band name to answer the question “Which band was Paul in”, from the information shown in Figure 1. A fine-grained named entity …
How to Increase Customer Acquisition and Retention with UDA
T Roosevelt – Unstructured Data Analytics: How to Improve …, 2018 – Wiley Online Library
… and the conversion Assess multicollinearity Replace and Impute variables Perform Text Analytics on the unstructured data Predict Conversion Score Use Machine Learning techniques such as Logistic Regression Decision Tree, Support Vector Machine, Neural Network …
An algorithmic approach to estimate cognitive aesthetics of images relative to ground truth of human psychology through a large user study
T Osman, SS Psyche, T Deb, A Firoze… – Journal of Information …, 2018 – Taylor & Francis
… 421–424). New York, NY, ACM. [Google Scholar]) introduced ACQUINE for real-time aesthetics classification. It is based on a support vector machine (SVM) classifier and involves fast feature extraction and classification. The …
Neural networks and deep learning
CC Aggarwal – 2018 – Springer
Page 1. Neural Networks and Deep Learning Charu C. Aggarwal A Textbook Page 2. Neural Networks and Deep Learning Page 3. Charu C. Aggarwal Neural Networks and Deep Learning A Textbook 123 Page 4. Charu C. Aggarwal …
Security for Machine Learning-based Systems: Attacks and Challenges during Training and Inference
F Khalid, MA Hanif, S Rehman… – … Conference on Frontiers …, 2018 – ieeexplore.ieee.org
… system vulnerability towards security threats [8]-[11]. Some example are: Amazon echo hacking [8], Facebook chatbots [8], self- driving bus crashes (on its very first day in Las Vegas) [13]. These real- world incidents highlight the …
Temporality-enhanced knowledgememory network for factoid question answering
X Duan, S Tang, S Zhang, Y Zhang, Z Zhao… – Frontiers of Information …, 2018 – Springer
… Navigli and Velardi (2010) presented a lattice-based approach to defini- tion and hypernym extraction. Huang et al. (2007) integrated textual features to represent the candi- date QA pairs and used a support vector machine (SVM) to classify QA pairs …
Task-Oriented Dialog Agents Using Memory-Networks and Ensemble Learning
RFG Meléndez – 2018 – pdfs.semanticscholar.org
… state of the art on bAbI tasks 5 and 6. User input comes usually as text, mostly due to the use of chatbots on commercial … Figure 2.2: Rasa task oriented chatbot architecture (Bocklisch et al., 2017 … These features are then fed to a classifier, such as an Support Vector Machine (SVM …
Sneak into Devil’s Colony-A study of Fake Profiles in Online Social Networks and the Cyber Law
MA Wani, S Jabin, G Yazdani, N Ahmadd – arXiv preprint arXiv …, 2018 – arxiv.org
… They can be used to assist the internet users as well. For example, chatbots [103] can be used to help students to answer their day-to-day queries and the bots which are developed for daily activities like weather update (eg Twitter bots) are the examples of good bots …
Advanced Data Analytics Using Python
S Mukhopadhyay – Springer
… TABLE OF CONTENTS Page 7. vii Naive Bayes Classifier …..61 Support Vector Machine …..62 Nearest Neighbor Classifier …..64 …
Benchmarking authorship attribution techniques using over a thousand books by fifty Victorian era novelists
A Gungor – 2018 – scholarworks.iupui.edu
… University Challenge organized by Roche. We have created a data driven and visu- ally stunning chatbot. Thank you team, for your hard work and making our time at Purdue worthwhile … differently between English and American authors. Support vector machine classifiers …
Model Averaging in Large Scale Learning
E Grappin – 2018 – pastel.archives-ouvertes.fr
… image recognition, object detection and trajectory decision. The state of the art algorithms to achieve these operations use Machine Learning algorithms such as support vector machine, as in Levinson et al. (2011), and/or neural networks, as in Pomerleau (1991) …
Intelligent interactive multimedia systems and services 2017
G De Pietro, L Gallo, RJ Howlett, LC Jain – 2018 – Springer
… “A Forward-Selection Algorithm for SVM-Based Question Classification in Cognitive Systems”–“A Model of a Social Chatbot”) focused on … 373 Nouha Arfaoui and Jalel Akaichi A Taxonomy of Support Vector Machine for Event Streams Classification …
Optimized Decision Making on Real Estate Data Using Data Analytics
G Kaur – 2018 – tudr.thapar.edu
… approaches are Decision trees, Bayesian classification, Backpropagation method, Support Vector Machine, k Nearest Neighbor, Neural Networks, Rule-based, Genetic algorithms … In the majority of the cases, you converse with a chatbot … Then, the chatbots propel with time …
Measuring Short Text Semantic Similarity with Deep Learning Models
J Ge – 2018 – yorkspace.library.yorku.ca
Page 1. Measuring Short Text Semantic Similarity with Deep Learning Models Jun Ge A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS …
Orange Technologies (ICOT)
M Dong, L Wang, Y Lu, H Li – ieeexplore.ieee.org
… Retrieval Peizhi Hu, Shaozhen Ye, Liang-Chih Yu and K.Robert Lai #08 Exploring Microscopic Fluctuation of Facial Expression for Mood Disorder Classification Ming-Hsiang Su, Chung-Hsien Wu, Kun-Yi Huang, Qian-Bei Hong and Hsin-Min Wang #09 A Chatbot Using LSTM …
Emotion and Sentiment Analysis from Twitter Text
K Sailunaz – 2018 – prism.ucalgary.ca
… Ortony, Clore and Collins SVM Support Vector Machine NLP Natural Language Processing … terrorists by analyzing the emotions of people after a terrorist attack or crime; improving the performances of chatbots and other automatic feedback systems; and so on. For instance …
Extracting data governance information from Slack chat channels
S Quigley – 2018 – pdfs.semanticscholar.org
… These classifiers were trained and tested using an annotated dataset of approximately 200,000 messages, and found a support vector machine based classifier to have the best … Decision Tree Classifier 0.7 0.69 0.7 Support Vector Machine 0.76 0.75 0.75 Page 22. 15 …
Spoilage Detection in Raspberry Fruit Based on Spectral Imaging Using Convolutional Neural Networks
KKJ Prakash – 2018 – arrow.dit.ie
… Traditionally in the field of agriculture, computer vision techniques have been implemented with machine learning models like Support Vector Machine (SVM) (Zhang … Hence, they are used in the fields of healthcare, creating chatbots and so on. DL techniques …
Creating an Emotion Responsive Dialogue System
A Vadehra – 2018 – uwspace.uwaterloo.ca
… Customer support or food ordering chatbots are examples of task spe- cific conversational agents where the success of the system is determined by the ability of the agent to complete its task [70] … Learner Models: SVM : Support Vector Machine, MNB : Multinomial Naive Bayes …
Creation and development of an AI teaching assistant
E Benedito Saura – 2018 – upcommons.upc.edu
… SVM Support Vector Machine … Turing’s ideas helped start the Chatbots revolution [3 … The first Chatbot, ELIZA was created in 1966, it could simulate the responses of a psy- chotherapist and could carry a conversation convincingly with a human [4]. In the 70s, ELIZA met its first non …
DynamicSlide: Exploring the Design Space of Reference-based Interaction Techniques for Slide-based Lecture Videos
H Jung, HV Shin, J Kim – Proceedings of the 2018 Workshop on …, 2018 – juhokim.com
Page 1. DynamicSlide: Exploring the Design Space of Reference-based Interaction Techniques for Slide-based Lecture Videos Hyeungshik Jung School of Computing, KAIST Daejeon, Republic of Korea hyeungshik.jung@kaist.ac.kr …
Big data processing with apache spark
S Penchikala – 2018 – books.google.com
Page 1. BIG-DATAPROCESSING WITH APACHE SPARK Srini Penchikala InfoC) ENTERPRISE SOFTWARE DEVELOPMENT SERIES Page 2. Big-Data Processing with ApacheSpark Srini Penchikala Page 3. Big-Data Processing with Apache Spark © 2018 Srini Penchikala …
Introduction to Deep Learning Business Applications for Developers
A Vieira, B Ribeiro – 2018 – Springer
… 6.5 Self-Driving Cars …..153 6.6 Conversational Bots (Chatbots) ….155 6.7 News Chatbots …..159 …
Beware of SMOMBIES: Verification of Users Based on Activities While Walking
E Klieme, C Tietz, C Meinel – … On Trust, Security And Privacy In …, 2018 – ieeexplore.ieee.org
… contribution is the distinction of all considered activities into three distinct subsets and a specific one-class Support Vector Machine per subset … addition, we created six real-world survey step interfaces to simulate situations for instant messaging (simple chat bot), reading articles …
Contextual Advertising Engine
GAA Rodrigues – 2018 – estudogeral.sib.uc.pt
… RCS – Rich Communication Service SVM – Support Vector Machine WE – Word Embedding … The surface of it is being scratched by Customer Support Chat Bots, but there is still much work to do in order to understand and exploit this channel’s full potential …
A cognitive assistant for learning java featuring social dialogue
M Coronado, CA Iglesias, Á Carrera… – International Journal of …, 2018 – Elsevier
Skip to main content …
Detecting Poisoning Attacks on Machine Learning in IoT Environments
N Baracaldo, B Chen, H Ludwig… – … Congress on Internet …, 2018 – ieeexplore.ieee.org
… significantly decrease overall performance, cause targeted misclassification or bad behavior, and insert backdoors and neural trojans [1], [2], [3], [4], [5], [6], [7]. A well-publicized example of a poisoning attack outside IoT occurred when Microsoft released Tay, a chat bot, to learn …
Applications of IoT in Healthcare
PS Mathew, AS Pillai, V Palade – … Computing for Big Data Systems Over …, 2018 – Springer
… learning, reasoning and human-machine interaction so it relies on technologies such as voice recognition, Natural language processing, computer vision, neural networks, Bayesians statistics, a range of machine learning methods, support vector machine, voting algorithm, K …
Machine Learning for Decision Makers: Cognitive Computing Fundamentals for Better Decision Making
P Kashyap – 2018 – books.google.com
… 108 Logistic (Classification) and Linear Regression….. 110 Support Vector Machine Algorithms….. 113 Naïve Bayes …
Artificial Intelligence for All: An Abiding Destination
V Pathak, P Tiwari – 2018 – books.google.com
Page 1. ARTIFICIAL INTELLIGENCE FOR ALL AN ABIDING DESTINATION º Nº. -º- 2 º nº 2 wº º: DR. PANKAT TIWARI VIKAS PATHAIK Page 2. Artificial Intelligence For All Artificial Intelligence For All i Page 3. Artificial Intelligence …
Recommendation Systems in a Conversational Web
KN Vavliakis, MT Kotouza, AL Symeonidis, PA Mitkas – 2018 – issel.ee.auth.gr
… time. Alongside “hyper-personalization” another term, “conversational web” has recently started to be used in the context of user interfaces, also known as chat- bots or virtual assistants, as well as in the context of web services …
A Vietnamese adjective emotion dictionary based on exploitation of Vietnamese language characteristics
VN Phu, VTN Chau, VTN Tran, ND Dat – Artificial Intelligence Review, 2018 – Springer
… An automated system for measuring semantic orientation would have application in text classification, text filtering, tracking opinions in online discussions, analysis of survey responses, and automated chat systems (chatbots) …
Artificial Intelligence and Social Simulation: Studying Group Dynamics on a Massive Scale
J Hoey, T Schröder, J Morgan… – Small Group …, 2018 – journals.sagepub.com
Recent advances in artificial intelligence and computer science can be used by social scientists in their study of groups and teams. Here, we explain how develo…
Recursive neural networks for density estimation over generalized random graphs
M Bongini, L Rigutini, E Trentin – IEEE transactions on neural …, 2018 – ieeexplore.ieee.org
… An attempt to synthesize probabilistic, logical, and relational learning (mostly rooted in the field of inductive logic programming) is found in [26]. Finally, kernels for structured data [27] could be used within the so-called “one-class” support vector machine framework. II …
Deep Learning in Skin Lesion Classification Tasks
R Vanheule – 2018 – lib.ugent.be
Page 1. Renée Vanheule Deep Learning in Skin Lesion Classification Tasks Academic year 2017-2018 Faculty of Engineering and Architecture Chair: Prof. dr. ir. Herwig Bruneel Department of Telecommunications and Information Processing …
M. KANM
M KANMAZ – 2018 – etd.lib.metu.edu.tr
… 32 Page 13. ix 3.3.5. Decision Trees ….. 32 3.3.6. Support Vector Machine….. 33 3.4 … 33 Figure 9- Support Vector Machine Hyperplane ….. 34 …
Cross-domain deep face matching for banking security systems
JS Oliveira – repositorio.unb.br
… SCDL: Semi-coupled Dictionary Learning. SVM: Support Vector Machine. TMR: True Matching Rate … ing signals, Anti-money Laundering (AML), Counter-terrorism Financing (CTF) and Fraud Detection, Chatbots, Credit scoring and Regulatory compliance. 8 Page 25 …
Beyond Automation: The Cognitive IoT. Artificial Intelligence Brings Sense to the Internet of Things
PKD Pramanik, S Pal, P Choudhury – … for Big Data Systems Over IoT, 2018 – Springer
… Bayesian Statistics, Hidden Markov, Neural Network, Support Vector Machine, Decision Tree, Principle Component Analysis, k-mean algorithm, etc., are the popular examples of the different algorithms and techniques in ML …
Efficient Large-Scale Stance Detection in Tweets
Y Yan, J Chen, ML Shyu – International Journal of Multimedia Data …, 2018 – igi-global.com
… theauthoruseddescriptivestatisticsmethodsandconcludedthatTrump’s campaignknewmoreabout howtouseTwitterchatbots … includingdiscriminantanalysisclassifier(DAC),linearregression,logistic regression(Meng&Shyu, 2012),aswellassupportvectormachine(SVM)(Suykens …
Sentiment classification with word localization based on weakly supervised learning with a convolutional neural network
G Lee, J Jeong, S Seo, CY Kim, P Kang – Knowledge-Based Systems, 2018 – Elsevier
… Experimental results show that the CNN-based document classification model achieved higher classification accuracies than the conventional machine learning-based models, such as the support vector machine or conditional random field, and other deep neural network …
Research on Decision-Making of Complex Venture Capital Based on Financial Big Data Platform
T Luo – Complexity, 2018 – hindawi.com
… network, the stock premium in 20 months is predicted and compared with the values predicted by support vector machine regression (SVR … can also learn to control robots, analyze images, summarize documents, recognize videos and handwriting, run chat bots, predict diseases …
DeepSumm: a deep learning approach to text summarization
R CAMPO – 2018 – politesi.polimi.it
… SVM Support Vector Machine … From everyday use applications like Google Translate and chatbots like Siri, Cortana and Alexa, to more challenging tasks like … more attention from non-IT industry too, as, for example, many company websites now feature a chatbot for customer …
Integrated Telegram and Web-based Forum with Automatic Assessment of Questions and Answers for Collaborative Learning
MLF Cheong, JYC Chen, BT Dai – 2018 IEEE International …, 2018 – ieeexplore.ieee.org
… four ML algorithms to predict the thoughtfulness score including, Linear Regression (LR), Neural Network Regression (NN), Support Vector Machine (SVM) and … Thus, to achieve both objectives, we plan to use the chat-bot to post questions from a question bank periodically to …
Network traffic profiling and anomaly detection for cyber security
L D’hooge – 2018 – lib.ugent.be
Page 1. Network traffic profiling and anomaly detection for cyber security Laurens D’hooge Student number: 01309688 Supervisors: Prof. dr. ir. Filip De Turck, dr. ir. Tim Wauters Counselors: Prof. dr. Bruno Volckaert, dr. ir. Tim Wauters …
Automatic Conversation Review for Intelligent Virtual Assistants
IR Beaver – 2018 – digitalrepository.unm.edu
… that of human reviewers and multiple aspects of system deployment for commercial use are discussed. Page 7. vi Contents List of Figures xiii List of Tables xviii Thesis Statement 1 1 Introduction 2 2 Background 7 2.1 Chatbot or IVA . . . . . 8 …
Interrupting Drivers for Interactions: Predicting Opportune Moments for In-vehicle Proactive Auditory-verbal Tasks
A Kim, W Choi, J Park, K Kim, U Lee – … of the ACM on Interactive, Mobile …, 2018 – dl.acm.org
Page 1. 175 Interrupting Drivers for Interactions: Predicting Opportune Moments for In-vehicle Proactive Auditory-verbal Tasks AUK KIM, KAIST, South Korea WOOHYEOK CHOI, KAIST, South Korea JUNGMI PARK, Samsung …
Detection and classification of harmful bots in human-bot interactions on Twitter
L CANNONE, M DI PIERRO – 2018 – politesi.polimi.it
… 57 5.1.4 Support Vector Machine … Gartner estimates that by 2020 85% of customer requests will be handled by bots, while Inbenta estimates 1.8 billion unique customer chatbot users by 2021 [2]. The technological advancements of chatbots undoubtedly produced …
AI4D: Artificial Intelligence for Development
S Mann, M Hilbert – Available at SSRN 3197383, 2018 – papers.ssrn.com
Page 1. Electronic copy available at: https://ssrn.com/abstract=3197383 Artificial Intelligence for Development: AI4D Martin Hilbert & Supreet Mann University of California, Davis, March 20, 2018 (hilbert@ucdavis.edu) ARTIFICIAL INTELLIGENCE: THE THEORY 3 …
Python Artificial Intelligence Projects for Beginners: Get up and running with Artificial Intelligence using 8 smart and exciting AI applications
J Eckroth – 2018 – books.google.com
Page 1. Python Artificial Intelligence Projects for Beginners and running with Artificial Intelligence using 8 smart and exciting A applications Page 2. Python Artificial Intelligence Projects for Beginners Get up and running with …
Novel Neural Techniques for Gene Expression Analysis in Cancer Prognosis
E Piccolo, G Cirrincione, A Bertotti, G Ciravegna… – webthesis.biblio.polito.it
… models are very limited in what they can represent, and that most of the programs that one may wish to learn cannot be expressed as a continuous geometric morphing of a data manifold” [15] As partial proof of it, an important project as the full-service chatbot M developed by …
The First Financial Narrative Processing Workshop (FNP 2018)
M El-Haj, P Rayson, A Moore – 2018 – lrec-conf.org
… Proposed framework is used in our in-house German language banking and finance chatbots. General challenges of German language processing and finance-banking domain chatbot language models and lexicons are also introduced …
Compassionate Artificial Intelligence: Frameworks and Algorithms
A Ray – 2018 – books.google.com
… Now, we are taking the help of AI everywhere, not even knowing about it. It is heavily active in search engines, social media, chat bots, medical diagnosis and even built right into our smartphones. Now, AI is at the core of Google’s search algorithms …
Natural Language Data Management and Interfaces
Y Li, D Rafiei – Synthesis Lectures on Data Management, 2018 – morganclaypool.com
Page 1. Natural Language Data Management and Interfaces Yunyao Li Davood Rafiei L I • R AFIE I N A T UR AL L ANGU A GE D A T A MAN A GE ME N T AND IN T E R F A CE SM O R GAN & CL A YPOO L HV Jagadish, Series Editor Page 2. Page 3. Natural Language …
Text-based sentiment analysis and music emotion recognition
E Çano – arXiv preprint arXiv:1810.03031, 2018 – arxiv.org
… misclassified. In works like [21], Adaboost which is the most common boosting implementation is reported to yield better improvements than bagging. Roughly at the same time, Support Vector Machine (SVM) classifier was in- vented and proven to be highly effective [22] …
Depth Inclusion for Classification and Semantic Segmentation
M Lotz – 2018 – diva-portal.org
… image. Traditional computer vision algorithms used many of these filters to obtain high dimensional vector of features for the input image, and then it would pass these to, eg. a support vector machine, for classification. ConvNets …
Alzheimer’s Disease Diagnosis Based on Cognitive Methods in Virtual Environments and Emotions Analysis
JMF Montenegro – arXiv preprint arXiv:1810.10941, 2018 – arxiv.org
… MRI Magnetic Resonance Imaging OCC One Class Classification OCSVM One-Class Support Vector Machine PCA Principal Component Analysis … SLUMS Saint Louis University Mental Status SVM Support Vector Machine t-SNE t – distributed Stochastic Neighbor Embedding …
Het leren van representaties voor symbolische sequenties
C De Boom – 2018 – biblio.ugent.be
… S ST Short Term SVD Singular Value Decomposition SVM Support Vector Machine Page 24. xviii T tf Term Frequency tf-idf Term Frequency Inverse Document Frequency t-SNE t-Distributed Stochastic Neighbor Embedding W WAV Windows Wave Page 25. Page 26. Page 27 …
Predicting human decision-making: From prediction to action
A Rosenfeld, S Kraus – Synthesis Lectures on Artificial …, 2018 – morganclaypool.com
… Conversely, software agents, such as a chatbot mounted on a smartphone (eg, Siri), are nor pairedwithaphysicalbody.Theplatformonwhichanagentismountedcanhaveavasti mpacton its perception, actions and human interaction capabilities …
Deep Learning with Azure: Building and Deploying Artificial Intelligence Solutions on the Microsoft AI Platform
M Salvaris, D Dean, WH Tok – 2018 – books.google.com
… Take Unilever, for example: They have built a collection of chatbots with a master botto help their employees interact with human resources services and all services inside the enterprise. Jabil uses AI for quality control in the circuit board manufacturing process …
Engagement Recognition based on Multimodal Behaviors for Human-Robot Dialogue
K Inoue – 2018 – repository.kulib.kyoto-u.ac.jp
Page 1. Title Engagement Recognition based on Multimodal Behaviors for Human-Robot Dialogue( Dissertation_?? ) Author(s) Inoue, Koji Citation Kyoto University (????) Issue Date 2018-09-25 URL https://doi.org/10.14989/doctor.k21392 Right …
Solving University entrance assessment using information retrieval
IC Silveira – teses.usp.br
… 61 8.2 Chatbots … Markov Logic Networks MR Mathematical Reasoning MRR Mean Reciprocal Rank NDH Non-Deciding Heuristic POS Part-of-Speech QA Question Answering SQUABU Science Questions Appraising Basic Understanding SVM Support Vector Machine TC Text …
Online review analysis: how to get useful information for innovating and improving products?
T Hou – 2018 – tel.archives-ouvertes.fr
Page 1. HAL Id: tel-02014508 https://tel.archives-ouvertes.fr/tel-02014508 Submitted on 11 Feb 2019 HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci- entific research documents, whether they are pub- lished or not …
Predictive Market Capitalization by Topic Analysis forClients’ Engagement in Financial Industries
J Santhappan – 2018 – search.proquest.com
Page 1. PREDICTIVE MARKET CAPITALIZATION BY TOPIC ANALYSIS FOR CLIENTS’ ENGAGEMENT IN FINANCIAL INDUSTRIES A Dissertation Presented in Partial Fulfillment of the Requirements for the Degree of Doctor of Computer Science By Jayasri Santhappan …
A study on the impact of domain knowledge incorporation
E Piret – 2018 – lib.ugent.be
… Springer, 2016, pp. 186–194. [13] Phan Thanh Noi and Martin Kappas, “Comparison of random forest, k- nearest neighbor, and support vector machine classifiers for land cover classification using sentinel-2 imagery,” Sensors, vol. 18, no. 1, pp. 18, 2017 …
Hardening quantum machine learning against adversaries
N Wiebe, RSS Kumar – New Journal of Physics, 2018 – iopscience.iop.org
… used to inform a model. Perhaps one of the most notable examples of this is the Tay chat bot incident. Tay was a chat bot designed to learn from users that it could freely interact with in a public chat room. Since the bot was programmed …
Towards a new generation of movie recommender systems: A mood based approach
N Wietreck – 2018 – diva-portal.org
Page 1 …
Symbiotic Artificial Intelligence and Its Challenges in Cybersecurity and Malware Research
AN Merrill – 2018 – search.proquest.com
… To get past problems like poisoning, researchers Chen et al. (2018) devised three different ML classifiers using support vector machine (SVM), random forest (RF), and K-nearest neighbor (KNN) to be trained on the types of data being fed to an AI model. By training on the data …
Systems and methods for SPIT detection in VoIP: Survey and future directions
MA Azad, R Morla, K Salah – Computers & Security, 2018 – Elsevier
Skip to main content …
A Survey on Food Computing
W Min, S Jiang, L Liu, Y Rui, R Jain – arXiv preprint arXiv:1808.07202, 2018 – arxiv.org
Page 1. A Survey on Food Computing WEIQING MIN, Key Lab of Intelligent Information Processing, Institute of Computing Technology, CAS, China SHUQIANG JIANG, Key Lab of Intelligent Information Processing, Institute of …
A Study of Methods in Computational Psychophysiology for Incorporating Implicit Affective Feedback in Intelligent Environments
DP Saha – 2018 – vtechworks.lib.vt.edu
Page 1. A Study of Methods in Computational Psychophysiology for Incorporating Implicit Affective Feedback in Intelligent Environments Deba Pratim Saha Doctoral Dissertation submitted to the Faculty of the Virginia Polytechnic …
A study of EU data protection regulation and appropriate security for digital services and platforms
M Westerlund – 2018 – doria.fi
Page 1. Magnus Westerlund A Study of EU Data Protection Regulation and Appropriate Security for Digital Services and Platforms M ag nus W esterlund | A Study of EU Data Protection Regulation and Appropriate Security for Dig ital Services and Platforms | 2018 Page 2 …
Rationale in Developers’ Communication
RMA Alkadhi – 2018 – d-nb.info
Page 1. Technische Universität München Fakultät für Informatik Lehrstuhl für Angewandte Softwaretechnik Rationale in Developers’ Communication Rana Mohammed A Alkadhi Vollständiger Abdruck der von der Fakultät für …
Mass Personalization through Mobile App Adoption Analytics
RM Frey – 2018 – research-collection.ethz.ch
… Once at the office, your personal chatbot has already answered some questions from employees and customers. That leaves time for coffee in the lunch room … The above-mentioned agenda can play as active a role as the car, the social network or the chatbot …
Dynamic Search Models and Applications
J Luo – 2018 – repository.library.georgetown.edu
Page 1. Dynamic Search Models and Applications A Dissertation submitted to the Faculty of the Graduate School of Arts and Sciences of Georgetown University in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science By Jiyun Luo, MS …
Fintech and Procurement Finance 4.0
B Nicoletti – Procurement Finance, 2018 – Springer
The future of procurement finance is connected to the digital transformation, which in the case of procurement finance is a digital revolution connected with Business 4.0. The correct concept is to…
Deep Learning in Information Security
S Thaler, V Menkovski, M Petkovic – arXiv preprint arXiv:1809.04332, 2018 – arxiv.org
Page 1. DEEP LEARNING IN INFORMATION SECURITY APREPRINT Stefan Thaler, Vlado Menkovski Eindhoven University of Technology Milan Petkovic Eindhoven University of Technology, Philips Research Laboratories September 13, 2018 ABSTRACT …
Machine learning in the real world with multiple objectives
T Bolukbasi – 2018 – search.proquest.com
… Penn Treebank RL . . . . . Reinforcement Learning SVM . . . . . Support Vector Machine WBC . . . . . Weighted Binary Classification xxi Page 23. 1 Chapter 1 Introduction Over the last decade, we have experienced an explosion in the availability and scale …
Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging
SJ Al’Aref, K Anchouche, G Singh… – European heart …, 2018 – academic.oup.com
Abstract. Artificial intelligence (AI) has transformed key aspects of human life. Machine learning (ML), which is a subset of AI wherein machines autonomously.
Examining Personality Differences in Chit-Chat Sequence to Sequence Conversational Agents
X Yujie – 2018 – eprints.illc.uva.nl
… Examples for task-oriented CA are chat- bots for booking restaurants or flights, where a conversation is closed once the agent has finished the task … algorithms, such as linear regression, M5′ regression tree, and support vector machine with linear kernels …
Using supervised machine learning and sentiment analysis techniques to predict homophobia in portuguese tweets
VG Pereira – 2018 – bibliotecadigital.fgv.br
… are increasing accuracy and the capability of distinguishing between meaning and the context of words), text classification (algorithms that organize and categorize information), question answering (every day more popular with Siri systems, Ok Google, chat bots and virtual …
Learning to Hash for Large-Scale Medical Image Retrieval
S Conjeti – 2018 – mediatum.ub.tum.de
Page 1. Dissertation Learning to Hash for Large-Scale Medical Image Retrieval Sailesh Conjeti Computer Aided Medical Procedures Prof. Dr. Nassir Navab Fakultät für Informatik Technische Universität München Page 2. Page 3. Technische Universität München …
Automatic Poetry Classification Using Natural Language Processing
V Kesarwani – 2018 – ruor.uottawa.ca
… ii Page 3. precision of 0.759 and a recall of 0.804 in identifying one type of metaphor in poetry, by using a Support Vector Machine classifier with various types of features … Entity detection are used in automated chat bots, content analyzers, etc …
4REAL 2018 Workshop on Replicability and Reproducibility of Research Results in Science and Technology of Language
A Branco, N Calzolari, K Choukri – 2018 – lrec-conf.org
Page 1. LREC 2018 Workshop 4REAL 2018 Workshop on Replicability and Reproducibility of Research Results in Science and Technology of Language PROCEEDINGS Edited by António Branco, Nicoletta Calzolari and Khalid Choukri ISBN: 979-10-95546-21-4 …
Computational reinforcement learning using rewards from human feedback
SA Raza – 2018 – opus.lib.uts.edu.au
… 167 A Support Vector Machine 173 B Proof of Theorem 3.1 176 … (non-embodied robotic agents) have already taken over an indispensable role in our society. From recommendation systems to chat-bots, they are ubiquitous in the computational applications (Aronson et al …
Deep Learning with Azure
M Salvaris, D Dean, WH Tok – Springer
… Take Unilever, for example: They have built a collection of chat bots with a master bot to help their employees interact with human resources services and all services inside the enterprise. Jabil uses AI for quality control in the circuit board manufacturing process …
Selecting and Generating Computational Meaning Representations for Short Texts
C Finegan-Dollak – 2018 – deepblue.lib.umich.edu
Page 1. Selecting and Generating Computational Meaning Representations for Short Texts by Catherine Finegan-Dollak A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy …
Shedding Light on Black Box Machine Learning Algorithms: Development of an Axiomatic Framework to Assess the Quality of Methods that Explain Individual …
M Honegger – arXiv preprint arXiv:1808.05054, 2018 – arxiv.org
… DL models have leveraged many of the most complex tasks, such as autonomous cars, robots and drones, chat-bots, and object and speech recognition. The different types of AI introduced above can be used to solve increasingly compli- cated problems …