Gradient Boosting & Chatbots 2019


Notes:

Gradient boosting is a machine learning technique for regression and classification problems, which produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees. It builds the model in a stage-wise fashion like other boosting methods do, and it generalizes them by allowing optimization of an arbitrary differentiable loss function.

Resources:

Wikipedia:

See also:

AI Algorithms Meta Guide


Diabot: A Predictive Medical Chatbot using Ensemble Learning
M Bali, S Mohanty, S Chatterjee, M Sarma… – academia.edu
… Chatbots have seen an unprecedented growth over the years as shown in Fig 1 and … Therefore, in this work we present a NLU-based chatbot which engages with the … DT), Random forest(RF), K-nearest neighbour(KNN), Logistic regression (LR) and Gradient boosting (GB) are …

A survey on construction and enhancement methods in service chatbots design
Z Peng, X Ma – CCF Transactions on Pervasive Computing and …, 2019 – Springer
… 7b). They deployed a Gradient Boosting Decision Tree (Ye et al … Two multi-chatbot frameworks: aAliMe Chat that uses an attentive Seq2Seq model as the re-ranker (Qiu et al … 2017); b an ensemble of retrieval-based and generation-based chatbots that use a decision tree as the re …

EMMA: An Emotion-Aware Wellbeing Chatbot
A Ghandeharioun, D McDuff… – 2019 8th …, 2019 – ieeexplore.ieee.org
… text-based interventions, either by a human or a chat-bot, have shown … in the BL quadrant of Russel’s circumplex model of emotion, the chatbot would recommend an … Ridge, Lasso, Elastic Net), Bayesian Ridge, Support Vector Regression, Gradient Boosting, AdaBoost, Random …

Using passive smartphone sensing for improved risk stratification of patients with depression and diabetes: cross-sectional observational study
A Sarda, S Munuswamy, S Sarda… – JMIR mHealth and …, 2019 – mhealth.jmir.org
… Using all the derived sensing variables, the extreme gradient boosting machine-learning classifier provided the best performance with an average cross-validation accuracy of 79.07% (95% CI 74%-84%) and test accuracy of 81.05% to classify symptoms of depression …

Knowledge retention through observation of instant messaging systems
J Costa, RP Duarte, C Cunha, J Menoita – Proceedings of the 23rd Pan …, 2019 – dl.acm.org
… Random Forest classifier (RFC) 0.900 0.658 Gradient Boosting classifier (GBC) 0.936 0.833 … Real conversations with ar- tificial intelligence: A comparison between human–human online conversations and human–chatbot conversations … Chatbots: are they really useful …

Machine Learning Implications for Banking Regulation
L McPhail, J McPhail – Available at SSRN 3423413, 2019 – papers.ssrn.com
… 15 Page 16. Random Forests and Gradient Boosting lead many applications of ML within the finance industry … User experience has been enhanced through mobile as FinTech firms and traditional banks expand the use of Chatbots, digital banking, and personalized experience …

Data-oriented and Machine Learning Technologies in FinTech
M Verma – FinTechs and an Evolving Ecosystem, 2019 – idrbt.ac.in
… gestures, spoken words and the language used by the user–these chatbots are now … There are however, numerous challenges in implementing an effective chatbot due to several … handle this problem of credit risk modelling includes–random forest, gradient boosting and deep …

Insurance: models, digitalization, and data science
H Albrecher, A Bommier, D Filipovi?… – European Actuarial …, 2019 – Springer
… Besides, in most methods, from Extreme Gradient Boosting techniques for lapse rates prediction to Kohonen maps for policyholders clustering … This is something that many insurance companies have already implemented and where automated advice via chatbots, ie computer …

Multiple Generative Models Ensemble for Knowledge-Driven Proactive Human-Computer Dialogue Agent
Z Dai, W Liu, G Zhan – arXiv preprint arXiv:1907.03590, 2019 – arxiv.org
… Generative method for building conversation chatbots has attracted increasing interest due to its great … For a knowledge-driven dialogue chatbot, an important ability is to reuse the … We employed a Gradient Boosting Decision Tree (GBDT) regressor (Friedman, 2001) to score the …

Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow: Concepts, tools, and techniques to build intelligent systems
A Géron – 2019 – books.google.com
… 189 Bagging and Pasting 192 Bagging and Pasting in Scikit-Learn 194 Out-of-Bag Evaluation 195 Random Patches and Random Subspaces 196 Random Forests 197 Extra-Trees 198 Feature Importance 198 Boosting 199 AdaBoost 200 Gradient Boosting 203 Stacking 208 …

MSc in Computer Science
RB Sulaiman – researchgate.net
… CHAPTER INFORMATION IN THIS CHAPTER ? Overview ? Chatbot system ? Chatbot technology ? Types of chatbot ? Comparison of chatbots ? Functions of chatbot ? Syntactic analysis ? Vector space model ? Machine learning models ? Support vector machines (SVM) …

The missing pieces of artificial intelligence in medicine
C Gilvary, N Madhukar, J Elkhader… – Trends in pharmacological …, 2019 – Elsevier
… Specifically, chat bots, which leverage a specialized area of AI called natural language processing (NLP … work of Ni et al., in which they created Mandy, a chat bot that will … Decision-tree-based models (random forest, gradient boosting, rotation forest, etc.) have been successful in …

Fraud detection for job placement using hierarchical clusters-based deep neural networks
J Kim, HJ Kim, H Kim – Applied Intelligence, 2019 – Springer
… Learning-based methods include various machine learning models such as decision tree, logistic regression, support vec- tor machine (SVM), gradient boosting, random forest, neural networks (NN), and convolution neural networks (CNN) [17–19] …

Hansjörg Albrecher, Antoine Bommier, Damir Filipovi?, Pablo Koch-Medina
S Loisel, H Schmeiser – ivw.unisg.ch
… Besides, in most methods, from Extreme Gradient Boosting techniques for lapse rates prediction to Kohonen Author’s personal copy Page 8 … via chatbots, ie computer programs that are designed to simulate conversation with human users, can help to save time and effort …

Glaucoma diagnosis using transfer learning methods
A Singh, S Sengupta… – Applications of Machine …, 2019 – spiedigitallibrary.org
… successful in various tasks such as image classification, semantic analysis of texts, virtual assistants, chatbots, object detection … It achieved a better performance than traditional machine learning (ML) techniques including random forests (RF), gradient boosting, support vector …

Ensemble-based method of answers retrieval for domain specific questions from text-based documentation
I Safiulin, N Butakov, D Alexandrov… – Procedia Computer …, 2019 – Elsevier
… high-tech companies from different fields to provide smart assistants or chatbots to accompany … Many companies want or prefer to use chatbot systems to provide smart assistants … algorithms with classical machine learning alternatives – SVM, decision trees, gradient boosting, etc …

Big Five Personality Traits and Ensemble Machine Learning to Detect Cyber-Violence in Social Media
R Zarnoufi, M Abik – International Conference Europe Middle East & North …, 2019 – Springer
… And by the introduction of a virtual psychological assistance in the form of a Chatbot, they can discuss with this person to know … XGBoost: Extreme Gradient Boosting is a decision tree based ML technique for regression and classification problems, which aims to produce a strong …

Digital Phenotyping as a Tool for Personalized Mental Healthcare
AM Bernardos, M Pires, D Ollé, JR Casar – Proceedings of the 13th EAI …, 2019 – dl.acm.org
… In the second case [5], it uses a Gradient boosting classifier, using as input the number and duration of calls, incoming and outcoming, text … Context information combined with chatbots can trigger new questions to eg check that the user is doing well in potentially risky situations …

Introducing MANtIS: a novel multi-domain information seeking dialogues dataset
G Penha, A Balan, C Hauff – arXiv preprint arXiv:1912.04639, 2019 – arxiv.org
… The results, Table 5, show that the best performing model is BERT, with a 0.13 absolute improvement in precision over the second best-performing model, the Gradient Boosting with bag-of-words model. Regarding models that …

Machine Learning at the Edge
M Levy, F Naiser – Software Engineering for Embedded Systems, 2019 – Elsevier
… Today there are chatbots able to converse on various topics that might be indistinguishable from a human. In some specific domains machines have even surpassed human performance, but only on a well-trained, given task (eg, image classification, translation) …

using Python
MPUD Kumar – academia.edu
Page 1. Manaranjan Pradhan U Dinesh Kumar | Manaranjan Pradhan U Dinesh Kumar| Machine Learning using Machine Learning Python using Python Page 2. Machine Learning using Python Page 3. Page 4. Machine Learning using Python Manaranjan Pradhan …

How to overcome modelling and model risk management challenges with artificial intelligence and machine learning
D Mayenberger – Journal of Risk Management in Financial …, 2019 – ingentaconnect.com
… Automated customer servicing: Assign customers to the right service representative by recognising their reason for calling, or chatbots that emulate a human interlocutor in an interactive customer service chat … Like the random forest, gradient boosting methods combine …

Anomaly Dataset Augmentation Using the Sequence Generative Models
SU Shin, I Lee, C Choi – 2019 18th IEEE International …, 2019 – ieeexplore.ieee.org
… that analyzes input data and a decoder that generates data, and the model works well in translator or chatbot … It includes many algorithms such as ensemble-based algorithms (eg, AdaBoost, Gradient- Boosting, RandomForest, and ExtraTree), naive bayes- based algorithm (eg …

Robot-controlled acupuncture—an innovative step towards modernization of the ancient traditional medical treatment method
KC Lan, G Litscher – Medicines, 2019 – mdpi.com
… visualization. (1) Symptom input: The user interacts with a chatbot on the smartphone to describe her/his symptoms … Each tree-based regressor is learned using the gradient boosting tree algorithm [24]. 2.6.6. Fitting 3DMM. 2D …

1, 2 Department of Computer Science, Parvathy’s Arts and Science College, Dindigul, Tamilnadu. 3Sky (Simplified Kundalini Yoga), World Community Service …
SG Gowri, R Devi, K Sethuraman – 2019 – ijrar.org
… Using different methods, such as regression, classification, gradient boosting, and prediction, supervised learning uses … because Messenger has become something of an experimental testing laboratory for chatbots. Any developer can create and submit a chatbot for inclusion in …

Advanced Methods of Statistical Machine Learning and Applications
A Fanzott – 2019 – netlibrary.aau.at
… also provide solutions for highly difficult tasks in image (eg face recognition)-, audio (eg chatbots)-, and video processing (eg autonomous driving). Though machine … decision theory in general. Ensemble learning methods, like AdaBoost or Gradient Boosting, are introduced in …

The Importance of Context When Recommending TV Content: Dataset and Algorithms
MS Kristoffersen, SE Shepstone… – IEEE Transactions on …, 2019 – ieeexplore.ieee.org
… contextual settings of TV viewing events, eg Bluetooth trackers to identify present users and their activity level, together with chatbot sessions for … Four methods are compared using scikit-learn [41] implementa- tions: logistic regression (LR), gradient boosting decision trees …

Generate, Filter, and Rank: Grammaticality Classification for Production-Ready NLG Systems
A Challa, K Upasani, A Balakrishnan… – arXiv preprint arXiv …, 2019 – arxiv.org
… Another important facet of acceptabil- ity is the naturalnesss (or human likeness) of the response, that can improve the usability of chatbots and other dialogue systems … 2001. Greedy function approxima- tion: a gradient boosting machine … A deep reinforcement learning chatbot …

Semantselt kahekordsete küsimuste kindlakstegemine: Quora juhtumi uurimine
NMH Ansari – 2019 – web-proxy.io
… sorting user- generated contents online. It can be helpful to build automatic chatbots that reply to user queries online and thus reduces the human effort by avoiding to cater to each individual’s queries. User can search for their …

Exploring ways to convey medical information during digital triage: A combined user research and machine learning approach
L Ansved, K Eklann – 2019 – diva-portal.org
Page 1. UPTEC STS 19026 Examensarbete 30 hp Juni 2019 Exploring ways to convey medical information during digital triage A combined user research and machine learning approach Linn Ansved Karin Eklann Page 2. Teknisk …

FinBrain: when finance meets AI 2.0
X Zheng, M Zhu, Q Li, C Chen, Y Tan – Frontiers of Information Technology …, 2019 – Springer
… They combined the static and dy- namic features of bidding lenders into a gradient boosting decision tree (GBDT) framework … recognition and natural language processing enable machine-to- human communication via interactive smart Q&A interfaces (eg, chatbot systems …

Personality assessment from social media data: An ensemble model
S Taghikhani – 2019 – search.proquest.com
… Neural Network and (CNN 1D), etc. For prediction, they tried many techniques such as Gradient Boosting, SVM, etc. Also, 10-fold cross validation dividing 10% into testing data and 90% into training data. For accuracy improvement, they also used …

AI: A Glossary of Terms
V Farhang-Razi, P Algra – Clinical Medicine Covertemplate, 2019 – Springer
… Chatbot Chatbot, also known as interactive agent, is an artificial intelligence system that uses natural language processing techniques to conduct a conversation via audio or texts. The most recognizable examples of chatbots are Apple’s Siri, Microsoft’s Cortana, and Amazon’s …

Enhanced answer selection in CQA using multi-dimensional features combination
H Fan, Z Ma, H Li, D Wang, J Liu – Tsinghua Science and …, 2019 – ieeexplore.ieee.org
… description. (3) We build a model from these features using the machine learning approaches, Support Vector Machine (SVM), Gradient Boosting Decision Tree (GBDT), and random forest, to classify the dimensions obtained …

Using Machine Learning and Artificial Intelligence in Production Technology
SR Sapkota – 2019 – theseus.fi
… investers have never seen before. Chatbot, tracking goods, analyzing supply chain agent behaviours, tracking the … learning library that contains boosting, decision tree learning, gradient boosting trees, expectation-maximization algorithm, k-nearest neighbour algorithm, naive …

Job Recommendation through Progression of Job Selection
A Nigam, A Roy, H Singh… – 2019 IEEE 6th International …, 2019 – ieeexplore.ieee.org
… They applied Gradient Boosting Machines (GBM) and used user, item and user-item interaction features in Deep Neural Networks (DNN), predicting whether a candidate will … al. [9], these embeddings are generated using Word2Vec model trained on a dataset of chatbot queries …

End-to-end Gated Self-attentive Memory Network for Dialog Response Selection
S Sun, YC Tam, J Cao, C Yan, Z Fu, C Niu, J Zhou – 2019 – cs.utah.edu
… Ke, G.; Meng, Q.; Finley, T.; Wang, T.; Chen, W.; Ma, W.; Ye, Q.; and Liu, T.-Y. 2017. LightGBM: A highly efficient gradient boosting decision tree … Se- quential matching network: A new architecture for multi- turn response selection in retrieval-based chatbots …

Corporate IT-support Help-Desk Process Hybrid-Automation Solution with Machine Learning Approach
K Shanmugalingam, N Chandrasekara… – 2019 Digital Image …, 2019 – ieeexplore.ieee.org
… Tickets will be created for admin-groups. The issue will be solved using automated messages through a chat bot solution … 3) XGBoost: XGBoost is a decision-tree-based ensemble Machine Learning algorithm that uses a gradient boosting framework …

Learn TensorFlow 2.0
IM Learning, P Singh, A Manure – Springer
… Boosted Trees with TensorFlow 2.0 …..47 Ensemble Technique …..47 Gradient Boosting ….. 49 …

Demand Forecasting using Random Forest and Artificial Neural Network for Supply Chain Management
N Vairagade, D Logofatu, F Leon… – International Conference …, 2019 – Springer
… These demand forecasting models were developed using Keras and scikit-learn packages in Python. The forecasting models used in this study are Gradient Boosting, Factorization Machines, and Deep Neural Networks [11] … 1. Chatbots for Operational Procurement. 2 …

Artificial intelligence for business
R Akerkar – 2019 – Springer
Page 1. SPRINGER BRIEFS IN BUSINESS 123 Rajendra Akerkar Arti cial Intelligence for Business Page 2. SpringerBriefs in Business Page 3. More information about this series at http://www.springer.com/series/8860 Page 4. Rajendra Akerkar Artificial Intelligence for Business …

A hybrid retrieval-generation neural conversation model
L Yang, J Hu, M Qiu, C Qu, J Gao, WB Croft… – Proceedings of the 28th …, 2019 – dl.acm.org
… al. [34]. Their proposed system uses a multi-seq2seq model to generate a response and then adopts a Gradient Boosting Decision Tree (GBDT) ranker to re-rank the gen- erated responses and retrieved responses. However …

R Machine Learning Projects: Implement supervised, unsupervised, and reinforcement learning techniques using R 3.5
SK Chinnamgari – 2019 – books.google.com
Page 1. R Machine Learning Projects Implement supervised, unsupervised, and reinforcement learning techniques using R 3.5 º Pacº – – º www.packticom Dr. Sunil Kumar Chinnamgari Page 2. R Machine Learning Projects Implement …

Interview choice reveals your preference on the market: To improve job-resume matching through profiling memories
R Yan, R Le, Y Song, T Zhang, X Zhang… – Proceedings of the 25th …, 2019 – dl.acm.org
Page 1. Interview Choice Reveals Your Preference on the Market: To Improve Job-Resume Matching through Profiling Memories Rui Yan ? Institute of Computer Science and Technology, Peking University Beijing, China ruiyan@pku.edu.cn Ran Le ? …

Efficient task-specific data valuation for nearest neighbor algorithms
R Jia, D Dao, B Wang, FA Hubis, NM Gurel, B Li… – arXiv preprint arXiv …, 2019 – arxiv.org
… In many real-world applications, the datasets that support queries and ML are often contributed by multiple individuals. One example is that complex ML tasks such as chatbot training often relies on massive crowdsourcing efforts …

ASAPPpy: a Python Framework for Portuguese STS.
J Santos, A Alves, HG Oliveira – ASSIN@ STIL, 2019 – ceur-ws.org
… by FCT’s INCoDe 2030 initiative, in the scope of the demon- stration project AIA, “Apoio Inteligente a empreendedores (chatbots)” … After initial experiments, three methods were tested, namely: a Support Vector Regressor (SVR), a Gradient Boosting Regressor (GBR) and a …

LIFELONG MACHINE LEARNING METHODS AND ITS APPLICATION IN MULTI-LABEL CLASSIFICATION
NM Chau – uet.edu.vn
… figuring out how to bring machine learning higher than ever. Applications, for example, intelligent assistants, chatbots, and physical robots that cooperate with humans and systems … cao h?n. Các ?ng d?ng nh? tr? lý thông minh, chatbot và robot v?t lý t??ng tác v?icon …

Natural Language Processing Fundamentals: Build intelligent applications that can interpret the human language to deliver impactful results
S Ghosh, D Gunning – 2019 – books.google.com
… Although you will continue to learn NLP-based techniques, the focus will gradually shift to developing useful applications. In those sections, you’ll gain an understanding of how to apply NLP techniques to answer questions, as can be used for chatbots …

Proceedings of the 11th International Workshop” Data analysis methods for software systems”
J Bernatavi?ien? – Vilnius University Proceedings, 2019 – zurnalai.vu.lt
Page 1. 11th International Workshop on DATA ANALYSIS METHODS FOR SOFTWARE SYSTEMS Druskininkai, Lithuania, Hotel “Europa Royale” http://www.mii.lt/DAMSS LITHUANIAN COMPUTER SOCIETY VILNIUS UNIVERSITY …

Machine Learning Architecture to Financial Service Organizations
K Palanivel – 2019 – academia.edu
… NLP powers the voice and text-based interface for virtual assistants and chatbots. NLP is increasingly being used to query data sets as well … The ML can be applied to customer support using chatbots, personalized experience and sentiment analysis …

Classification-based approach for Question Answering Systems: Design and Application in HR operations
LMA Heijden – 2019 – essay.utwente.nl
… These can be either so-called dialogue managers, where the chatbot responds based on a humanly designed way to certain intents defined by humans during the design [16, 17, 18]. Other chatbots generate answers using machine learning techniques such as …

How Technologies Will Change the Way Finance Departments Work: A Target Picture and Guidelines for Digital Finance
MA Eßwein – 2019 – duepublico2.uni-due.de
… 83 4.4. Gradient boosting ….. 84 4.5 … RQ Research question TAM Technology acceptance model XGbar Extreme gradient boosting time series forecasting Specific to use case two BCI Business confidence index …

Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging
SJ Al’Aref, K Anchouche, G Singh… – European heart …, 2019 – 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.

Application of Apriori and FP-growth algorithms in soft examination data analysis
X Yang, X Lin, X Lin – Journal of Intelligent & Fuzzy Systems, 2019 – content.iospress.com
… Real conversations with artificial intelligence: A comparison between human–human online conversations and human–chatbot conversations, Computers … Xia , M. Elhoseny , X. Yuan and L. Gu , Feature selection based on artificial bee colony and gradient boosting decision tree …

Safety evaluation model for smart driverless car using support vector machine
W Gang – Journal of Intelligent & Fuzzy Systems, 2019 – content.iospress.com
… Real conversations with artificial intelligence: A comparison between human-human online conversations and human–chatbot conversations, Computers … Xia , M. Elhoseny , X. Yuan and L. Gu , Feature selection based on artificial bee colony and gradient boosting decision tree …

Heuristic decision tree model for ecological urban green space network construction
B Sun, J Qian, K Qu, GM Draper – Journal of Intelligent & …, 2019 – content.iospress.com
… Real conversations with artificial intelligence: A comparison between human–human online conversations and human–chatbot conversations, Computers in … Xiao-hui Yuan and Lichuan Gu , Feature selection based on artificial bee colony and gradient boosting decision tree …

Practical Machine Learning with Rust: Creating Intelligent Applications in Rust
J Bhattacharjee – 2019 – books.google.com
… TABLE OF CONTENTS Chapter 5: Natural Language Processing…..187 5.1 Sentence Classification…..188 5.2 Named Entity Recognition…..201 5.3 Chatbots and Natural …

Data-and expert-driven analysis of cause-effect relationships in the production of lithium-ion batteries
T Komas, R Daub, MZ Karamat… – 2019 IEEE 15th …, 2019 – ieeexplore.ieee.org
… variables and 604 cells with an average capacity of 26,67Ah; xGb stands for extreme Gradient boosting and refers to the implementation of gradient boosting machines, GLM … storey, and a. ZagalsNy, Ihow software Developers mitigate collaboration Friction with chatbots,” Feb …

MOLI: Smart Conversation Agent for Mobile Customer Service
G Zhao, J Zhao, Y Li, C Alt, R Schwarzenberg… – Information, 2019 – mdpi.com
Human agents in technical customer support provide users with instructional answers to solve a task that would otherwise require a lot of time, money, energy, physical costs. Developing a dialogue system in this domain is challenging due to the broad variety of user questions. Moreover …

Towards effective and interpretable person-job fitting
R Le, W Hu, Y Song, T Zhang, D Zhao… – Proceedings of the 28th …, 2019 – dl.acm.org
… 3.2 Intention Model Unlike the matching scenarios in Question Answering [11, 28] and Retrieval Based Chatbot [17, 18], where the target is to find a proper answer for a certain query. The scenario of Person-Job Fit is a two-side matching procedure, the appropriate fit relies on …

Hateful People or Hateful Bots? Detection and Characterization of Bots Spreading Religious Hatred in Arabic Social Media
N Albadi, M Kurdi, S Mishra – Proceedings of the ACM on Human …, 2019 – dl.acm.org
… While some bots can be bene cial (eg, customer service chatbots), the focus in this work is on content-polluter bots that mimic human behavior … Note that we also experimented with other regression algorithms such as logistic regression and gradient boosting regression trees …

Exploring the value of the Bregman Block Average Co-clustering algorithm for missing value imputation in geo-referenced time series
JM Timmermans – 2019 – dspace.library.uu.nl
… agery. • Text analysis: filtering spam emails and customer support chat-bots. • Data mining, finding disease patterns in medical data … 12 Chapter 2. Literature review Gradient boosting algorithms predict a class or continuous variable by combining multiple algorithms. Combin …

Deep Learning For Dummies
JP Mueller, L Massaron – 2019 – books.google.com
Page 1. Deep Learning by John Paul Mueller and Luca Massaron 0004332690.INDD April 5, 2019 12:10 PM i Trim size: 7.375 in × 9.25 in Page 2. Deep Learning For Dummies® Published by: John Wiley & Sons, Inc., 111 River …

Digital interventions for mental disorders: key features, efficacy, and potential for artificial intelligence applications
DD Ebert, M Harrer, J Apolinário-Hagen… – Frontiers in …, 2019 – Springer
… 2. Virtual or augmented reality interventions for exposure to feared stimuli [46, 47, 48]. 3. Serious games, training psychological strategies in a video game format [49]. 4. Avatar-led therapy sessions [50] or chatbot-mediated interventions [51]. 5 …

Distributed traffic forecasting using Apache Spark
N Boufidis – 2019 – repository.ihu.edu.gr
… 5.1.2 Random Forest Regression ….. 30 5.1.3 Gradient Boosting Trees Regression ….. 30 … telligence applications like fully or semi-autonomous vehicles, to clever, humanlike chat- bots like Apple’s Siri and Microsoft’s Cortana …

SYNTHNOTES: TOWARDS SYNTHETIC CLINICAL TEXT GENERATION
KA Brown – 2019 – trace.tennessee.edu
… intelligence research for decades. Among the most famous examples is the ELIZA [5] chatbot developed at the MIT Artificial Intelligence lab in the 1960’s. Using only the 2 … Over the following decades, NLG applications have moved beyond simple chatbot programs and have …

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 humans can be deceived in thinking that they are … The ELIZA chatbot (Weizenbaum 1976) or contestants to the Loeb- ner Prize competition (Stephens 2004) are dialog systems which rely on …

A Machine Learning Approach to Identifying Novel Therapeutics and Their Underlying Mechanisms
CM Gilvary – 2019 – search.proquest.com
… A) The use of drug similarity properties to predict if two drugs will share an indication using a gradient boosting model … Page 23. 13 Drug pairs that share indications can be predicted by model Using these diverse drug properties as features we trained a Gradient Boosting model …

Web Engineering: 19th International Conference, ICWE 2019, Daejeon, South Korea, June 11–14, 2019, Proceedings
M Bakaev, F Frasincar, IY Ko – 2019 – books.google.com
… Keywords: Deep learning 4 Technical debt 1 Introduction Deep learning has shown amazing results in many areas including image classification [10], object detection [12], pose estimation, machine translation [4], chatbots [5], sentiment analysis, recommendation [11] and …

Can AI Solve the Diversity Problem in the Tech Industry: Mitigating Noise and Bias in Employment Decision-Making
KA Houser – Stan. Tech. L. Rev., 2019 – HeinOnline
… It proposes that algorithmic- based decisions are the key to increasing diversity in the tech industry and Using Machine Learning Algorithms: A Case for Extreme Gradient Boosting, 5 INT’L J. ADVANCED RES. ARTIFICIAL INTELLIGENCE 22, 26 (2016) …

Data-driven Marketing Content: A Practical Guide
L Wilson – 2019 – books.google.com
Page 1. MARKETN c C O N T EN T Page 2. DATA-DRIVEN MARKETING CONTENT: A PRACTICAL GUIDE Page 3. Praise for Data-driven Marketing Content: A Practical Guide Lee has been my go-to guy for search marketing …

Explainability in human–agent systems
A Rosenfeld, A Richardson – Autonomous Agents and Multi-Agent …, 2019 – Springer
… These systems, often called human–agent systems or human–agent Cooperatives, have moved from theory to reality in the many forms, including digital personal assistants, recommendation systems, training and tutoring systems, service robots, chat bots, planning systems …

Machine learning methods for indoor occupancy detection with Co2 multi-sensor data
G Giardini – 2019 – politesi.polimi.it
… It would be very useful for you to know how many seats are available simply by consulting a web page or writing to a chatbot. This could often save you a lot of time … [13] Temperature, Light, Co2, Humidity Random Forest, Gradient Boosting Machines, Decision Tree 2 95%-99 …

Automatic Detection of Emotions and Distress in Textual Data
E Mohammadi – 2019 – caiac.ca
Page 1. Automatic Detection of Emotions and Distress in Textual Data Elham Mohammadi A Thesis in The Department of Computer Science and Software Engineering Presented in Partial Fulfillment of the Requirements for the Degree of Master of Computer Science at …

Prioritizing Hospital Incident Reports Through Text Classification
M Flood – 2019 – search.proquest.com
… This method of data exploration has many practical uses; some of the more famous implementations are spam filters and chatbots. 2.3.1 Natural Language Processing in Industry NLP is also being used with incident reports to try and automatically determine …

Gastroenterology Meets Machine Learning: Status Quo and Quo Vadis
A Adadi, S Adadi, M Berrada – Advances in bioinformatics, 2019 – hindawi.com
… In medicine, AI is essentially considered as a decision-support systems. In addition to ML techniques, AI provides other tools including robotic surgical systems, conversational AI (chatbots), and human brain interfaces that speed up the transition to the digital health …

Data Driven Computational Intelligence for Scientific Programming
A Rubio-Largo – downloads.hindawi.com
… ese data may be structured, semistructured, and/ or unstructured, extracted from sources as different as Natural Language Processing [2] (chatbots, comments, and social media), multimedia content (videos, images, and audio), geographic information systems (GIS), or sensors …

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 …

CA5211 C PROGRAMMING AND DATA STRUCTURES LABORATORY LTPC
P PO – DEPARTMENT OF INFORMATION SCIENCE AND … – management.ind.in
Page 38. CA5211 C PROGRAMMING AND DATA STRUCTURES LABORATORY LTPC 0 0 4 2 OBJECTIVES: • To introduce the concepts of structured programming language. • To develop skills in design and implementation of data structures and their applications …

LEGAL ISSUES AND COMPUTATIONAL MEASURES AT THE CROSS-SECTION OF AI, LAW AND POLICY
S Rathi – 2019 – web2py.iiit.ac.in
… It is important that autonomous systems remain value neutral. • Interactions: With the growing penetration of chat bots and other interactive forms of AI, it is a value add to these technologies if they can indulge in coherent and consistent interactions …

TOPIC MODELLING, SENTIMENT ANALSYS AND CLASSIFICATION OF SHORT-FORM TEXT
CJOFI PURCHASES, L STOYANOVA, W WALLACE – 2019 – local.cis.strath.ac.uk
… library, which features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy …

Text analytics with Python: a practitioner’s guide to natural language processing
D Sarkar – 2019 – books.google.com
… 306 Random Forest….. 307 Gradient Boosting Machines….. 308 Evaluating Classification Models …

Towards Agent Negotiators: A Machine Learning Framework for Analyzing Human Negotiation Tactics
Y Xu – 2019 – search.proquest.com
Page 1. Page 2. Page left intentionally blank. 2 Page 3. Towards Agent Negotiators: A Machine Learning Framework for Analyzing Human Negotiation Tactics By Yuyu Xu A dissertation submitted in partial fulfillment of the requirements for the degree of …

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