Naive Bayes & Chatbots 2019


See also:

100 Best Bayesian Tutorial Videos


Arabic Dialogue Act Recognition for Textual Chatbot Systems
A Joukhadar, H Saghergy, L Kweider… – Proceedings of The First …, 2019 – aclweb.org
Arabic Dialogue Act Recognition for Textual Chatbot Systems … In general, chat bot systems can be composed of three basic components: Natural Language Un … they implemented four classification methods including Random Forest, Support Vec- tor Machine, Naive Bayes, and …

An Approach for Building Effective Real Estate Chatbots in Vietnamese
TD Cao, QH Nguyen – Soft Computing for Biomedical Applications and …, 2020 – Springer
… https://techinsight.com.vn/khai-quat-cac-bai-toan-xu-ly-ngon-ngu-tu-nhien-trong-phat-trien-thong- chatbot/. 7. Evgeniou, T … Springer, Heidelberg (1999)Google Scholar. 8. Rish, I.: An empirical study of the naive Bayes classifier … Jurafsky, D., Martin, JH: Dialog systems and chatbots …

EMERGENCY PATIENT CARE SYSTEM USING CHATBOT
P Raj, R Murali Krishna, SM Krishna, KH Vardhan… – ijtre.com
… aid, offering a solution for simpler medical issues: these are all possible situations for chatbots to step … C. Multinomial Naive Bayes: Multinomial Naive Bayes is an algorithm for text classification and Natural language processing … An Approach to Enhance Chatbot Semantic Power …

KLOOS: KL Divergence-based Out-of-Scope Intent Detection in Human-to-Machine Conversations
EH Yilmaz, C Toraman – Proceedings of the 43rd International ACM …, 2020 – dl.acm.org
… Human- to-machine dialog systems, eg chatbots [16], incorporate decision making process to generate … BOW-NB is multinomial Naive Bayes classifier using TF-IDF features on BOW model … Chatbot using a knowledge in database: Human-to-machine conversation modeling …

CONVERSATIONAL CHATBOT SYSTEM FOR STUDENT SUPPORT IN ADMINISTRATIVE EXAM INFORMATION
HA Rasheed, J Zenkert, C Weber, M Fathi – researchgate.net
… Traditional text classification methods include naïve Bayes, support vector machine (SVM), and k- nearest neighbour … Page 8. [3] S. Abdul-Kader and Dr. John, “Survey on Chatbot Design Techniques in … [8] D. Jurafsky and J. Martin, “Dialog Systems and Chatbots,” Speech and …

Open Domain Chatbot Based on Attentive End-to-End Seq2Seq Mechanism
SS Abdullahi, S Yiming, A Abdullahi… – Proceedings of the 2019 …, 2019 – dl.acm.org
… Simple Machine Learning techniques like Support Vector Machines (SVM), linear regression and nai?ve Bayes methods learn the correlation … We therefore suggest that more data networked together can give the chatbot multi-domain intelligence to … Deep Learning for ChatBots …

Study on emotion recognition and companion Chatbot using deep neural network
MC Lee, SY Chiang, SC Yeh, TF Wen – MULTIMEDIA TOOLS AND …, 2020 – Springer
… In the past, chat bots can only handle simple information … To achieve intelligent medical practice, the Chatbot is further expected to be applied to the services … German, French, Spanish, and Thai, and the classi- fication methods include PCA, Naïve Bayes classifier, Spectrum …

Remote cardiovascular health monitoring system with auto-diagnosis
B Bhattacharya, S Mohapatra… – … on Vision Towards …, 2019 – ieeexplore.ieee.org
… Chatbots are generally used in dialog systems for various practical purposes and use sophisticated Natural Language … Figure 5. Chatbot Questionnaire … D.5. K-Means Clustering with Naive Bayes (KMNB) KMNB algorithm is implemented by summing classification and clustering …

Intent Detection-Based Lithuanian Chatbot Created via Automatic DNN Hyper-Parameter Optimization
J Kapo?i?t?-Dzikien? – Frontiers in Artificial Intelligence and …, 2020 – books.google.com
… Stochastic Gradient Descent, Nearest Centroid, Multinomial Naive Bayes, Bernoulli Naive Bayes, K-means … J. An Information Retrieval-based Approach for Building Intuitive Chatbots for Large … Li Z, Zhou J. DocChat: An Information Retrieval Approach for Chatbot Engines Using …

A Survey on Chat-Bot system for Agriculture Domain
PY Niranjan, VS Rajpurohit… – 2019 1st International …, 2019 – ieeexplore.ieee.org
… Fig.1 Flow of chat-Bot system Question Analysis … 2014 III. LITERATURE SURVEY Literature survey has been discussed in this section to highlight the work carried out till now in chatbot system … Experiment was conducted with Naïve-Bayes, random forest and decision trees …

Towards Emotion Intelligence in Neural Dialogue Systems
C Huang – 2019 – era.library.ualberta.ca
… hand-crafted rules. Dialog systems can be generally divided into open-domain systems and … building open-domain social chatbots has received much more attention from the research community … social textual chatbot XiaoIce [104] states that a mature chatbot should be …

Emotion Recognition Using Chatbot System
S Pophale, H Gandhi, AK Gupta – … of International Conference on Recent Trends … – Springer
… Jain [11]. ISEAR. Probabilistic classifier—Naïve Bayes algorithm. TFIDF. 80 … The developing trends indicate that chatbots will be matching providing similar services and human behavior … build with chatbot system and notify class also helpful for prevention. References …

A study of incorrect paraphrases in crowdsourced user utterances
MA Yaghoub-Zadeh-Fard, B Benatallah… – Proceedings of the …, 2019 – aclweb.org
… Also known as dialogue systems, virtual assistants, chatbots or simply bots (Campagna et al., 2017; Su et al., 2017 … Moreover, it is feasible to automatically generate pairs of questions and answers by mining datasets in the fields of Question Answering and dialog systems …

C-net: Contextual network for sarcasm detection
AK Jena, A Sinha, R Agarwal – Proceedings of the Second Workshop on …, 2020 – aclweb.org
… Sarcasm detection plays a crucial role in improving the effectiveness of chatbot systems … 64 Method Twitter Reddit Response Only Set Logistic Regression 0.685 0.622 Naive Bayes 0.673 0.626 SGD Classifier 0.668 … Yeah right: Sarcasm recognition for spoken dialogue systems …

If I Hear You Correctly: Building and Evaluating Interview Chatbots with Active Listening Skills
Z Xiao, MX Zhou, W Chen, H Yang, C Chi – Proceedings of the 2020 CHI …, 2020 – dl.acm.org
… models for 17 intents, each with four popular classification models: logistic regression, linear SVM, Adaboost, and Naïve Bayes … This chatbot demonstrated active listening on the four interview topics. Both chatbots asked the same interview questions in the same order …

Evaluation of Chatbot Prototypes for Taking the Virtual Patient’s History.
A Reiswich, M Haag – dHealth, 2019 – books.google.com
… which were already integrated in scikit- learn, including: Random Forest (RF), Naïve Bayes (NB), Linear … AS Lokman, JM Zain, FS Komputer and K. Perisian, Designing a Chatbot for diabetic … HN Io and CB Lee, Chatbots and Conversational agents: A bibliometric analysis, in …

Towards Social and Interpretable Neural Dialog Systems
A Saleh – 2020 – dash.harvard.edu
… Open-domain dialog generation is the problem of building chatbots that can communicate with humans … We view social deftness as a practical goal for dialog systems to avoid getting mired in … A social dialog system should be able to understand relationships and its role in them …

IMPLEMENTATION OF AN AUTOMATIC QUESTION ANSWERING SYSTEM USING MACHINE LEARNING
SA ABIR – 2019 – researchgate.net
… LIST OF FIGURES Figure 3.1: Workflow of Naive Bayes Classifier … 1. The closed domain chatbots are those which can reply to a limited number of … internal mechanism and classification of artificial intelligence services to build a chatbot to …

Passive Diagnosis of Mental Health Disorders Incorporating an Empathic Dialogue System
F Delahunty, M Arcan, R Johansson – 2019 – thesiscommons.org
… 3Commonly known as chatbots … par- ticipants from the public domain who had a short conversation with our proposed empathic dialogue system … To evaluate Hypothesis 2, we randomly allocated recruited participants to have conversations with one of two dialogue systems …

State Machine Based Human-Bot Conversation Model and Services
S Zamanirad, B Benatallah, C Rodriguez… – International Conference …, 2020 – Springer
… It can use any classification model such as Naive Bayes, MaxEntropy and Support Vector Machine … Ilievski, V., Musat, C., Hossmann, A., Baeriswyl, M.: Goal-oriented chatbot dialog management … A., Sànchez-Ferreres, J., Carmona, J., Padró, L.: From process models to chatbots …

Intelligent Chatbot for Requirements Elicitation and Classification
CSRK Surana, DB Gupta… – 2019 4th International …, 2019 – ieeexplore.ieee.org
… 75-78). IEEE. [10] Khan, R. and Das, A., 2018. Build Better Chatbots. Apress … [12] Setyawan, MYH, Awangga, RM and Efendi, SR, 2018, October. Comparison Of Multinomial Naive Bayes Algorithm And Logistic Regression For Intent Classification In Chatbot …

A Systematic Identification of Pedagogical Conversational Agents
LN Paschoal, AL Krassmann, FB Nunes… – aic-atlas.s3.eu-north-1.amazonaws …
… more space in the community and industry is conversational agents, also known as chatbots or dialogue … ((”conversational agent” OR chatbot OR ”chat … Pattern Matching and Rules created by the authors MASCARET meta-model Policy Iteration Naive Bayes RUANLP algorithm …

A comparative study of social bot classification techniques
F Örnbratt, J Isaksson, M Willing – 2019 – diva-portal.org
… Many such machine learning algorithms exist; Decision tree, Random forests, Naïve Bayes, K-Nearest Neighbour, Support Vector Machines or k-means … Web Robots (crawlers) ? Chatbots (natural language based dialog system) …

Intent Classification for Dialogue Utterances
J Schuurmans, F Frasincar – IEEE Intelligent Systems, 2019 – ieeexplore.ieee.org
… In order to classify intents of customers, a dialogue system needs to analyze the incoming … There is the Chatbot Corpus on Travel Scheduling, and the StackExchange Corpus on … and A. Wroblewska, “Multi- intent hierarchical natural language understanding for chatbots,” in Proc …

Towards emotion-sensitive conversational user interfaces in healthcare applications
K Denecke, R May, Y Deng – Studies in health technology and …, 2019 – arbor.bfh.ch
… The challenges of sentiment and emotion analysis in health chatbots have not yet been considered so far … They used a Naïve Bayes classifier based on su- pervised learning that was trained on a … of several types of data (audio, video, and text) from a chatbot’s environment has …

Doly: Bengali Chatbot for Bengali Education
M Kowsher, FS Tithi, MA Alam, MN Huda… – … on Advances in …, 2019 – ieeexplore.ieee.org
… As algorithms, we have used Naive Bayes classifier and … So, we compared ?Doly’ with two chatbots which are Neural Conversational Machine (NCM) and Cleverbot … a chatbot with the help of neural network technique as well as a sequence to sequence chatbot via Bengali …

Open Domain Conversational Chatbot
V Deshmukh, SJ Nirmala – International Conference on Information …, 2019 – Springer
… There is a huge range of chatbots identified based on the learning capacity and the manner of interaction … Porter used the Naïve Bayes supervised learning approach … Z., Duan, N., Bao, J., Chen, P., Zhou, M.: DocBot: an information retrieval approach for chatbot engines using …

Samvaadhana: A Telugu Dialogue System in Hospital Domain
SR Duggenpudi, KSS Varma, R Mamidi – … of the 2nd Workshop on Deep …, 2019 – aclweb.org
… 68.778% Naive Bayes+BOW+Unigrams 86.046% Naive Bayes+TFIDF+Unigrams 83.721% Naive Bayes+TFIDF+Bigrams 83.721% Naive Bayes+TFIDF+Both … Spoken dialogue system using recognition of user’s feedback for rhythmic dialogue … A neural-network based chat bot …

Commonsense properties from query logs and question answering forums
J Romero, S Razniewski, K Pal, J Z. Pan… – Proceedings of the 28th …, 2019 – dl.acm.org
… com/2018/03/17/facebook-and-youtube-should-learn-from-microsoft-tay-racist-chatbot … Another NLP application is dialog systems and chatbots (eg, [17]), where CSK adds plausibility priors … in the candidate gathering phase.7 These are used to train a naive Bayes model, which …

Predicting User Intents and Satisfaction with Dialogue-based Conversational Recommendations
W Cai, L Chen – Proceedings of the 28th ACM Conference on User …, 2020 – dl.acm.org
… authors identified four most-frequent user intents in a shopping chatbot (ie, recommendation … they may want to achieve when they interact with a dialogue system [15] … text classification [1], including Logistic Regression, Support Vector Machine (SVM), Naive Bayes, Decision Tree …

Dialogue quality and nugget detection for short text conversation (STC-3) based on hierarchical multi-stack model with memory enhance structure
HE Cherng, CH Chang – NTCIR14. p. to appear, 2019 – research.nii.ac.jp
… a plenty of time and human resources, and provide a 24-hour chatbot to answer … in NTCIR-12 as the first step toward natural language conversation for chatbots … on STC have investigated different techniques including: Hidden Markov Model [19], Naïve Bayes [12], Conditional …

Twitter Bots and the Swedish Election
J Fernquist, L Kaati, R Schroeder, N Akrami… – … Source Intelligence and …, 2020 – Springer
… web robots (crawlers and scrapers). chatbots (human-computer dialog system which operates through natural language via text or speech) … Different algorithms such as AdaBoost, logistic regression, support vector machines and naive Bayes have been tested …

Automatic summarization of medical conversations, a review
J Lopez – TALN-RECITAL 2019-PFIA 2019, 2019 – hal.archives-ouvertes.fr
… this serious game, the student establishes a conversation with the chatbot to establish … Recently Ramanujam & Kaliappan (2016) extended the application of the Naive Bayes algorithm to … developed to help the health field, such as intelligence agents and health dialog systems …

Towards task-sensitive assistance in public spaces
MA Kilian, M Kattenbeck, M Ferstl… – Aslib Journal of …, 2019 – emerald.com
… By using dialogue trees, we modeled interaction consisting of pre-defined chatbot messages and … helps us to overcome the aforementioned challenge of dialogue coherence in chatbots (see Section … 5.1.5 Contrasting theoretical models – Tree-augmented Naïve Bayes results …

Voice Based Chatbot for System Control
N Lokeswari, S Priyanka, K Amaravathi – ijresm.com
… It is because like the “Naive Bayes algorithm”, we have implemented it using predefined existing data, and also used the concept of Machine Learning … [5] https://www.expertsystem.com/chatbot/ [6] DeeAnn Allison, “Chatbots in the Library: is it time?,” 2011 …

A Deep Multi-task Model for Dialogue Act Classification, Intent Detection and Slot Filling
M Firdaus, H Golchha, A Ekbal, P Bhattacharyya – Cognitive Computation, 2020 – Springer
… To create robust human/machine dialogue systems or chatbots, it is essential to understand the … realistic and natu- ral utterances spoken by the speakers in a human/machine dialogue system … en- tropy models (MEMM) [1], Bayesian networks [12, 21, 25, 26], naive Bayes [4, 55 …

Short Text Conversation Based on Deep Neural Network and Analysis on Evaluation Measures
HE Cherng, CH Chang – arXiv preprint arXiv:1907.03070, 2019 – arxiv.org
… that evaluate the quality and structure of dialogue between a chatbot and a … With such measures, the quality of chatbots could be evaluated automatically and efficiently … have investigated different techniques including: Hidden Markov Model [2], Naïve Bayes [20], Conditional …

Empathic Response Generation in Chatbots.
T Spring, J Casas, K Daher, E Mugellini… – SwissText, 2019 – ceur-ws.org
… classifiers, such as the Support Vector Machine (SVM) (Teng et al., 2006), Naive Bayes, or Decision … We pointed out the four stages of the interaction with the chatbot and underlined the … On the construction of more human-like chatbots: Affect and emotion analy- sis of movie …

Development of customized conversational interfaces with Deep Learning techniques
P Cañas Castellanos – 2020 – e-archivo.uc3m.es
… With this platform, a complete chatbot is built in the form of an … Evaluation of the spoken dialog system with real users generates a very positive feed- back … Keywords: Conversational Interfaces, Spoken Dialog Systems, Machine learning, DialogFlow, Deep Learning, TensorFlow …

Influence of Time and Risk on Response Acceptability in a Simple Spoken Dialogue System
A Partovi, I Zukerman – Proceedings of the 20th Annual SIGdial Meeting …, 2019 – aclweb.org
… We describe a longitudinal user study con- ducted in the context of a Spoken Dialogue System for a … (2016) produced dialogue contributions of chat- bots; and Serban et al … types from the corpora collected in Stage 1 of our experiment (Section 3):7 Naïve Bayes, Support Vector …

A Novel Multi-agent-based Chatbot Approach to Orchestrate Conversational Assistants
JF Zolitschka – International Conference on Business Information …, 2020 – Springer
… 81.33. 79.76. Naïve Bayes. 88.78. 78.67 … 212–225 (2017)Google Scholar. 5. Dhanda, S.: How chatbots will transform the retail industry. Juniper Research (2018)Google Scholar. 6. Abdul-Kader, SA, Woods, JC: Survey on chatbot design techniques in speech conversation systems …

Adaptive dialogue management using intent clustering and fuzzy rules
D Griol, Z Callejas, JM Molina, A Sanchis – Expert Systems, 2020 – Wiley Online Library
… in mobile devices and smart speakers, educational tutoring agents, entertainment chatbots in open … 2004) and has been used to develop hundreds of successful commercial dialogue systems … based approaches are also an efficient alternative when the dialogue system must be …

Exploring machine learning and deep learning frameworks for task-oriented dialogue act classification
T Saha, S Srivastava, M Firdaus, S Saha… – … Joint Conference on …, 2019 – ieeexplore.ieee.org
… Applications such as online chat-bots that include the Problem Solving Agent, Conversational Agent, etc … tag-set is proposed which is more appropriate for building a chat-bot system … Naive Bayes approach was applied on SWBD corpus in [4], using tri-gram language model …

Chatbot Application on Cryptocurrency
Q Xie, D Tan, T Zhu, Q Zhang, S Xiao… – … IEEE Conference on …, 2019 – ieeexplore.ieee.org
… Chatbot knows the answer only because the input is in the associated pattern. Similarly, chatbots respond to anything related to the associated patterns, but it cannot go beyond the associated pattern … Naive Bayes is the classic algorithm for text classification …

Towards the Learning, Perception, and Effectiveness of Teachable Conversational Agents
N Chhibber – 2019 – uwspace.uwaterloo.ca
… Page 8. 3.2.1 Naive Bayes Classifier . . . . . 13 3.2.2 Proposed Approach . . . . . 17 3.3 Conversational Interface . . . . . 19 3.3.1 Why a Conversational Interface? . . . . 19 3.3.2 Dialog System …

Chatbot Interaction with Artificial Intelligence: Human Data Augmentation with T5 and Language Transformer Ensemble for Text Classification
JJ Bird, A Ekárt, DR Faria – arXiv preprint arXiv:2010.05990, 2020 – arxiv.org
… October 14, 2020 ABSTRACT In this work, we present the Chatbot Interaction with Artificial Intelligence (CI-AI) framework as an approach to the training of deep learning chatbots for task classification. The intelligent system …

Artificial Intelligence for Text Analytics
MY Day – 2020 – ntpu.edu.tw
… 16 2020/12/31 (Question Answering and Dialogue Systems) 17 2021/01/07 I (Final Project Presentation I) … Entropy (ME) Naïve Bayes (NB) … Bot Maturity Model 54 Source: https://www. capgemini.com/2017/04/how-can-chatbots-meet-expectations-introducing-the-bot-maturity …

Knowledge Creation Model for Emotion Based Response Generation for AI
UK Premasundera, MC Farook – 2019 19th International …, 2019 – ieeexplore.ieee.org
… Zhou and colleagues [21] at Tsinghua University in Beijing have developed a chatbot that can evaluate … When considering classification techniques; algorithms such as Naive Bayes (NB), Support Vector Machine (SVM); use bag … 22] A. Pardes, “The Emotional Chatbots Are Here …

FastText-Based Intent Detection for Inflected Languages
K Balodis, D Deksne – Information, 2019 – mdpi.com
… require a large amount of training data, which is not the typical case for chatbots … accuracy and use it as the main metric to compare the different dialogue system providers … The chatbot dataset contains users’ questions from a Telegram chatbot that answers questions related to …

Hierarchical reinforcement learning for open-domain dialog
A Saleh, N Jaques, A Ghandeharioun, J Shen… – Proceedings of the …, 2020 – ojs.aaai.org
… A successful open- domain dialog system could provide enormous value en- abling more natural … also unlock new, beneficial applications of AI, such as companion chatbots for therapy … model for producing toxic responses as determined by a Naive Bayes- Logistic Regression …

Estimating Conversational Styles in Conversational Microtask Crowdsourcing
S Qiu, U Gadiraju, A Bozzon – Proceedings of the ACM on Human …, 2020 – dl.acm.org
… called Guardian, which enables both expert and non-expert workers to collaboratively translate Web APIs into a dialogue system format [22] … A previous work based on Facebook Messenger used a Chatbot to connect learners and experts, for providing experts’ feedback to …

Chichang Jou
MY Day – 2020 – mail.tku.edu.tw
… 15 2020/06/08 (Question Answering and Dialogue Systems) 16 2020/06/15 I (Final Project Presentation I) … Entropy (ME) Naïve Bayes (NB) … Bot Maturity Model 52 Source: https://www. capgemini.com/2017/04/how-can-chatbots-meet-expectations-introducing-the-bot-maturity …

Developing an LSTM-based Classification Model of IndiHome Customer Feedbacks
A Arifianto, S Suyanto, A Sirwan… – … Conference on Data …, 2020 – ieeexplore.ieee.org
… complaints classification using modified nazief-adriani stemming algorithm and naive bayes classifier,” Journal … 9034616 [23] YW Chandra and S. Suyanto, “Indonesian Chatbot of University … Data Augmentation to Improve a Question Retrieval in Short Dialogue System,” in 2019 …

The Neural Network Conversation Model enables the Commonly Asked Student Query Agents
N Muangnak, N Thasnas, T Hengsanunkul… – researchgate.net
… Even though modern chatbots employ … Better the prediction model accuracy using comparison-based methods, Naïve Bayes and decision tree, the dialogue patterns from different tutors could be varied … Tangkathach [10] presented the learning portal system for the chatbot …

Socially-Aware Dialogue System
R Zhao – 2019 – lti.cs.cmu.edu
… However, social chatbots fall short in replicating the interpersonal function of communication … SAPA) This chapter reviews our knowledge-inspired socially-aware dialogue system in a … recognition of conversational strategies in the service of a socially-aware dialog system …

Practical Natural Language Processing: A Comprehensive Guide to Building Real-World NLP Systems
S Vajjala, B Majumder, A Gupta, H Surana – 2020 – books.google.com
… Pipeline Using Existing Text Classification APIs One Pipeline, Many Classifiers Naive Bayes Classifier Logistic … A Simple FAQ Bot A Taxonomy of Chatbots Goal-Oriented Dialog Chitchats A … for Building Dialog Systems Dialog Systems in Detail PizzaStop Chatbot Deep Dive …

Review on: Virtual Assistant and Patient Monitoring System by using AI & Data Science
S Patil, V Patil, V Bagal, S Butala – 2019 – academia.edu
… Keywords-: Artificial intelligence(AI), Data Science, Machine Learning; Naive Bayes algorithm for behavior … system uses Natural language processing, Machine learning for creating a chatbot … a. Methodology: This system uses the multi modal dialogue system which processes …

Latest Developments in Deep Learning in Finance 8th November 2019
NYU Courant – 2019 – pdfs.semanticscholar.org
… CLASSIFICATION Discriminant Analysis Naïve Bayes Nearest Neighbors CART … Machine translation • Spoken dialog systems • Complex question answering NLP in Industry … Speech recognition • Chatbots / Dialog agents • Automating customer support • Controlling devices …

Ambient Assisted Living with Deep Learning
E Merdivan – 2019 – tel.archives-ouvertes.fr
… utilisant des mod`eles statistiques et standardisés d’apprentissage de machine tels que Naive Bayes, Hidden Markov Models (HMM) et Conditional Random Fields (CRF) … and developing intelligent dialogue systems for AAL systems, with an emphasis on a …

Towards computational persuasion via natural language argumentation dialogues
A Hunter, L Chalaguine, T Czernuszenko… – Joint German/Austrian …, 2019 – Springer
… of an argument), we can train a classifier (eg a classification tree, a naive Bayes classifier, or … The other aspect of developing argumentation chatbots for persuasion is to hook-up the interface to … which the user selects his/her choice to be replaced by the chatbot natural language …

Natural Language Processing, Understanding, and Generation
A Singh, K Ramasubramanian, S Shivam – Building an Enterprise Chatbot, 2019 – Springer
… human-like conversation. Figure 5-1 shows an architecture that utilizes the techniques from NLP, NLU, and NLG to build an enterprise chatbot. Open image in new window Figure 5-1. Figure 5-1 Architecture diagram for chatbots …

AIA-BDE: A Corpus of FAQs in Portuguese and their Variations
HG Oliveira, J Ferreira, J Santos, P Fialho… – Proceedings of The …, 2020 – aclweb.org
… oriented questions and their variations, ready to be used in the evaluation of IR / QA dialogue systems … it could be used as plan B in a single-turn QA dialogue system: when no … Classifiers were learned with three different methods, namely a Linear SVM, a Naïve Bayes (NB) and …

Artificial Intelligence acceptance: morphological elements of the acceptance of Artificial Intelligence
MM Figueiredo – 2019 – repositorio.ucp.pt
… Some examples of supervised learning algorithms are logistic regression, naive bayes, random forest and artificial neural networks4 … Duolingo is a very well-known chatbot that allows people to learn and … to chatbots ranging from virtual agents and dialogue systems to machine …

Speech Command Classification System for Sinhala Language based on Automatic Speech Recognition
T Dinushika, L Kavmini… – … Conference on Asian …, 2019 – ieeexplore.ieee.org
… this speech command classification system and develop a speech dialog system for the … Setyawan, RM Awangga and SR Efendi, “Comparison Of Multinomial Naive Bayes Algorithm And Logistic Regression For Intent Classification In Chatbot,” International Conference on …

Named Entity Recognition and Relation Detection for Biomedical Information Extraction
N Perera, M Dehmer, F Emmert-Streib – Frontiers in Cell and …, 2020 – frontiersin.org
The number of scientific publications in the literature is steadily growing, containing our knowledge in the biomedical, health, and clinical sciences. Since there is currently no automatic archiving of the obtained results, much of this information remains buried in textual details not …

Transforming the communication between citizens and government through AI-guided chatbots
A Androutsopoulou, N Karacapilidis, E Loukis… – Government Information …, 2019 – Elsevier
… on various well-tried algorithms and techniques, including Neural Networks, K-means, Decision Trees, Naïve Bayes, and Support … blocks, the abovementioned services add intelligence to the functionality and user interfaces of existing chatbots (and chatbot builders), the …

InPHYNet: Leveraging attention-based multitask recurrent networks for multi-label physics text classification
V Udandarao, A Agarwal, A Gupta, T Chakraborty – Knowledge-Based Systems – Elsevier
… to-use form that can be utilized to build a question-answering physics chatbot, we prepared … an increasing focus on building end-to-end QA based interactive dialog systems for facilitating … of work has been pivoted on the Student Response Analysis (SRA) part of a dialog system …

Cap. 1. ARTIFICIAL INTELLIGENCE APPLICATIONS AND TOOLS IN HIGHER EDUCATION: AN OVERVIEW
N Romanov, MI Cluci, ID Anastasiei… – … educa?iei doctorale în … – sesyr.feaa.uaic.ro
… which could be related to personalized learning, students’ personal data, chat bots and even … a foreign language more efficiently with the use of human-machine dialogue systems … Tree (CART) algorithms, JRIP Decision Rule, Gradient Boosting Trees and NB (Naive Bayes) …

Adaptive and Personalized Systems Based on Semantics
P Lops, C Musto, F Narducci, G Semeraro – Semantics in Adaptive and …, 2019 – Springer
… Synset-based user profiles were learnt using a relevance feedback algorithm based on the Rocchio method [114] or a naïve Bayes classifier [69], and those models are able to classify new items as interesting or not with respect to the user preferences …

Detecting Abuse on the Internet: It’s Subtle
S Bagga – 2020 – search.proquest.com
Page 1. Detecting Abuse on the Internet: It’s Subtle Sunyam Bagga Master of Science School of Computer Science McGill University Montreal, Quebec December, 2019 A thesis submitted to McGill University in partial fulfillment …

Comparison and efficacy of synergistic intelligent tutoring systems with human physiological response
F Alqahtani, N Ramzan – Sensors, 2019 – mdpi.com
The analysis of physiological signals is ubiquitous in health and medical diagnosis as a primary tool for investigation and inquiry. Physiological signals are now being widely used for psychological and social fields. They have found promising application in the field of computer …

Computational Sarcasm Processing: A survey
KGP Bhattacharyya – cfilt.iitb.ac.in
… a sarcasm generation module (Sar- casmBot) for chatbots and mention that integrat- ing a sarcasm generation module allows existing chatbots to become … to train a variety of classi- fiers including linear SVM, logistic regression, de- cision tree, random forest and naive bayes …

Beneath the Tip of the Iceberg: Current Challenges and New Directions in Sentiment Analysis Research
S Poria, D Hazarika, N Majumder… – arXiv preprint arXiv …, 2020 – arxiv.org
… Sentiment- aware dialogue system Sentiment- aware style transfer … and unsupervised–have employed myriad of algorithms that include SVMs (Moraes et al., 2013a), Naive Bayes Clas- sifiers … 2.3 presents one such example where a user is chatting with a chit-chat style chatbot …

Recognition of cooking activities through air quality sensor data for supporting food journaling
F Gerina, SM Massa, F Moi… – Human-centric …, 2020 – hcis-journal.springeropen.com
… Indeed, we believe that these technologies, possibly coupled with automatic dialog systems, may provide adequate solutions for unobtrusive and privacy-conscious context recognition, as well as user engagement for supporting diet data acquisition on the long term …

Machine Learning from Casual Conversation
A Mohammed Ali – 2019 – stars.library.ucf.edu
… 105 Figure 6.2: Training and Testing Naïve Bayes Classifier, Decision Tree Classifier (DT) … There is a long history of studying conversational agents and chatbots. The earliest known chatbot was ELIZA [132], which was designed to emulate a Rogerian therapist …

“I think it might help if we multiply, and not add”: Detecting Indirectness in Conversation
P Goel, Y Matsuyama, M Madaio, J Cassell – … on Spoken Dialogue System …, 2019 – Springer
… following supervised machine learning algorithms—Logistic Regression, Naive Bayes, Random Forest … or a general-purpose socially-aware spoken dialogue system [30] that … in interpersonal communication, incorporating its detection in spoken dialogue systems may ultimately …

Towards inclusive education in the age of artificial intelligence: Perspectives, challenges, and opportunities
PS Mohammed – Artificial intelligence and inclusive education, 2019 – Springer
… In addition, computer-supported collaborative learning (CSCL) and dialogue systems were actively pursued particularly in feedback systems … (2016) used Naïve Bayes classifiers to … Home (a speaker and voice assistant), Cozmo (a robot toy) and Julie (a chatbot) affected the …

Conversational summarization for chatbots in a banking environment
M de Ruiter – 2020 – researchgate.net
… of Conversationality Conversationality is an important aspect of text summariza- tion in the context of chatbots … replies are selected, since they are mostly well written, and because the chatbot’s purpose is … The experimental setup uses a Naive Bayes (NB) classifier and an LSTM …

User intent prediction in information-seeking conversations
C Qu, L Yang, WB Croft, Y Zhang, JR Trippas… – Proceedings of the 2019 …, 2019 – dl.acm.org
… can only be extracted from the metadata of the forum, such as user authority level or answer votes, so that our method can be applicable to dialog systems … We adopt classic ML methods, including Naive Bayes classifier, SVM, random forest, and AdaBoost as baseline classifiers …

You talkin’to me? A practical attention-aware embodied agent
RR Divekar, JO Kephart, X Mou, L Chen… – IFIP Conference on Human …, 2019 – Springer
… data to characteristics of the conversation and trained and evaluated a Naive Bayes classifier … Radziwill and Benton (2017) have proposed a good approach to evaluating chatbots, involving evaluation … here was not to evaluate the conversation or capability of the chatbot as a …

Computational Sarcasm for Different Languages: A Survey
A Dubey, A Joshi, P Bhattacharyya – cfilt.iitb.ac.in
… They present a sarcasm genera- tion module (SarcasmBot) for chatbots and mention that integrating a sarcasm generation module allows existing chatbots to become more ‘human’. 4 Datasets In this section, we describe datasets for computational sar- casm … Naive Bayes …

Developing Amaia: A Conversational Agent for Helping Portuguese Entrepreneurs—An Extensive Exploration of Question-Matching Approaches for Portuguese
J Santos, L Duarte, J Ferreira, A Alves, HG Oliveira – Information, 2020 – mdpi.com
… 2. Related Work. Dialogue systems typically exploit large collections of text, often including conversations … In opposition to generative systems, IR-based dialogue systems do not handle very well requests for which there is no similar text in the corpus …

Adaptace jazykového modelu na téma v reálném ?ase
J Lehe?ka – 2019 – otik.uk.zcu.cz
… days. Typical applications, in which ASR is indispensable, are: (1) chatbots, virtual assis- tants and dialogue systems, where people are conversing with computers, (2) dictating systems, where people need to note a large amount of information without typing it …

A data-efficient deep learning approach for deployable multimodal social robots
H Cuayáhuitl – Neurocomputing, 2020 – Elsevier
… First, dialogue acts are derived from the most likely actions, Pr(a|s) > 0.001, with probabilities derived from a Naive Bayes classifier trained from example dialogues—see [1]. Second, all game moves were allowed from the subset of those not taken yet (to the robot’s knowledge) …

Diving Deep into Deep Learning: History, Evolution, Types and Applications
HCA Deekshith Shetty, MJ Varma, S Navi, MR Ahmed – researchgate.net
… Polynomial Regression Support Vector Machine (SVM) Support Vector Regression Kernel SVM Decision Tree Regression Naive Bayes Decision Tree Classification Random Forest Classification Unsupervised Learning Clustering Dimensionality Reduction K-Means Principal …

Efficient Algorithm for Answering Fact-based Queries Using Relational Data Enriched by Context-Based Embeddings
AA Altowayan – 2019 – webpage.pace.edu
… Page 3. Abstract Intelligent conversational systems – such as question answering and chatbots – are becoming a more critical component of today’s AI in areas ranging from health, medicine, and security, to personal assistants, and other domains …

Medical Instructed Real-Time Assistant for Patient with Glaucoma and Diabetic Conditions
UU Rehman, DJ Chang, Y Jung, U Akhtar… – Applied Sciences, 2020 – mdpi.com
… calls, and many more things [1]. Many applications from different domains currently have their own built-in virtual assistants such as televisions [2], mobile devices [3], vehicles [4], and the Internet of things [5,6]. The virtual assistant is also known as a chatbot, dialogue manager …

Artificial Intelligence in the legal sector. A comparative analysis of expert and AI approaches to predicting court decisions
N Kaliazina – 2019 – pdfs.semanticscholar.org
… ones such as spell checking, keyword search, information extraction from websites, documents classification, machine translation, spoken dialogue systems, and complex … classification algorithms (for example, support vector machines (SVM) or Naive Bayes) … chatbots that …

AI Enabled Foreign Language Immersion: Technology and Method to Acquire Foreign Languages with AI in Immersive Virtual Worlds
RR Divekar – 2020 – search.proquest.com
Page 1. AI ENABLED FOREIGN LANGUAGE IMMERSION: TECHNOLOGY AND METHOD TO ACQUIRE FOREIGN LANGUAGES WITH AI IN IMMERSIVE VIRTUAL WORLDS Rahul R. Divekar Submitted in Partial Fulfillment of the Requirements for the Degree of …

Recommendation in Dialogue Systems
Y Sun – 2019 – escholarship.org
… These chatbots are implemented on different platforms, such as mobiles, home devices, and webpages … method, the dialogue system, and their intersections. Chapter 3 introduces the … Another example is the machine learning based Naive Bayes approach [74] [69] …

LREC 2020 Workshop Language Resources and Evaluation Conference 11–16 May 2020
A Bhatia, S Shaikh – lrec2020.lrec-conf.org
… Goldwasser, 2019). Analysis of chatbot responses (Prakhar Gupta and Bigham, 2019) yields human-judgement correla- tion improvements. Approaches above differ from ours in that they require extensive model training. Our …

Critical Infrastructures Security: Improving Defense Against Novel Malware and Advanced Persistent Threats
G Laurenza – 2020 – iris.uniroma1.it
Page 1. Critical Infrastructures Security: Improving Defense Against Novel Malware and Advanced Persistent Threats Department of Computer, Control, and Management Engineering Antonio Ruberti, Sapienza – University of Rome …

A Review on Dyadic Conversation Visualizations-Purposes, Data, Lens of Analysis
JY Kim, RA Calvo, K Yacef, NJ Enfield – arXiv preprint arXiv:1905.00653, 2019 – arxiv.org
… Lastly, the nature of human-to-bot conversation can al- so be different from human-to-human conversations. In a general, unconstrained context, current dialogue systems are incapable of generating responses that are rated as highly appropriate by humans [45] …

Era of Intelligent Systems in Healthcare
S Belciug, F Gorunescu – … Decision Support Systems—A Journey to …, 2020 – Springer
The aim of this chapter is to prepare the reader for the outstanding trip that she/he embarked when starting reading this book. At first, we shall try to look for answers to some of the most…

Contextual language understanding Thoughts on Machine Learning in Natural Language Processing
B Favre – 2019 – hal-amu.archives-ouvertes.fr
… General purpose dialog agents, also known as “chatbots”, are a good example of how … The ELIZA chatbot (Weizenbaum 1976) or contestants to the Loeb- ner Prize competition (Stephens … valency assessment, predicting the quantity of silence required for a dialog system to take …

Intelligent Decision Support Systems: A Journey to Smarter Healthcare
S Belciug, F Gorunescu – 2020 – Springer
Page 1. Intelligent Systems Reference Library 157 Smaranda Belciug Florin Gorunescu Intelligent Decision Support Systems–A Journey to Smarter Healthcare Page 2. Intelligent Systems Reference Library Volume 157 Series Editors …

Deep learning for nlp and speech recognition
U Kamath, J Liu, J Whitaker – 2019 – Springer
Page 1. Uday Kamath · John Liu · James Whitaker Deep Learning for NLP and Speech Recognition Page 2. Deep Learning for NLP and Speech Recognition Page 3. Uday Kamath • John Liu • James Whitaker Deep Learning for NLP and Speech Recognition 123 Page 4 …

ICTAI 2019
YM Boumarafi, Y Salhi – computer.org
Page 1. 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI) ICTAI 2019 Table of Contents General Chair’s Foreword xxxvi Message from the ICTAI Program Chair xxxvii ICTAI 2019 Conference Committees xxxviii Program Area Chairs xxxix …

A Companion Robot for Modeling the Expressive Behavior of Persons with Parkinson’s Disease
AP Valenti – 2020 – search.proquest.com
… 107 Chapter 6 Improving Natural Language Understanding in Spoken Dialogue Systems 109 6.1 Introduction … xix Page 21. 6.1 Typical components of a spoken dialogue system. At each turn t, input speech is converted to an utterance, ut, which the Natural Lan …

Cognitive Computing Recipes
A Masood, A Hashmi – Springer
Page 1. Cognitive Computing Recipes Artificial Intelligence Solutions Using Microsoft Cognitive Services and TensorFlow — Adnan Masood Adnan Hashmi Foreword by Matt Winkler Page 2. Cognitive Computing Recipes Artificial Intelligence Solutions Using …

A Systematic Approach for Automatically Answering General-Purpose Objective and Subjective Questions
LP Acharya – 2019 – repository.lib.fit.edu
… 1960s by the MIT Artificial Intelligence Laboratory to demonstrate the communication between humans and machines. Similar to a chatbot, ELIZA uses pattern matching and substitution methodologies to simulate conversations. DOCTOR is an example of a script …

DEEP NEURAL NETWORD BASED NATURAL LANGUAGE INFERENCE MODEL
T BEKELE – 2020 – ir.bdu.edu.et
… NLU services in different domains and for different purposes, eg natural language inference [23], question answering for localized search [24], form driven dialogue systems [25], dialogue management [26], and the internet of things [27]. 2.2 …

Machine learning in mental health: A systematic review of the HCI literature to support the development of effective and implementable ML systems
A Thieme, D Belgrave… – ACM Trans. Comput …, 2020 – designandwellbeing.com
Page 1. 34 Machine Learning in Mental Health: A Systematic Review of the HCI Literature to Support the Development of Effective and Implementable ML Systems ANJA THIEME and DANIELLE BELGRAVE, Microsoft Research GAVIN DOHERTY, Trinity College Dublin …

Machine Learning in Mental Health: A Systematic Review of the HCI Literature to Support the Development of Effective and Implementable ML Systems
A Thieme, D Belgrave, G Doherty – ACM Transactions on Computer …, 2020 – dl.acm.org
Page 1. 34 Machine Learning in Mental Health: A Systematic Review of the HCI Literature to Support the Development of Effective and Implementable ML Systems ANJA THIEME and DANIELLE BELGRAVE, Microsoft Research GAVIN DOHERTY, Trinity College Dublin …

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