Logistic Regression & Chatbots 2019


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AI Algorithms Meta Guide


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 … with different features have been used to detect the correct speech act categories: Logistic Regression, SVM, Multi … In general, chat bot systems can be composed of three basic components: Natural Language Un …

Peculiarities of Human Machine Interaction for Synthesis of the Intelligent Dialogue Chatbot
I Sidenko, G Kondratenko, P Kushneryk… – 2019 10th IEEE …, 2019 – ieeexplore.ieee.org
… APIs such as IBM Watson, Microsoft Azure, and sci3it-learn for development chatbots … The chatbot is developed using programming language Python with the Tensorflow framewor3 … 8). Logistic regression as a natural language recognition module is used, which determines the …

Intelligent Dialogue System Based on Deep Learning Technology
I Sidenko – pdfs.semanticscholar.org
… Keywords: neural network, linguistic recognition, machine learning, deep learning, decision making, dialogue system, chat-bot … on using linguistic tricks to create characters for chat bots to enhance … To implement this node in the dialogue system, the logistic regression of text …

Effectiveness of a chat-bot for the adult population to quit smoking: protocol of a pragmatic clinical trial in primary care (Dejal@)
JF Avila-Tomas… – BMC Medical …, 2019 – bmcmedinformdecismak …
… A logistic regression model will be built to adjust for confounding factors … Since chat-bots “understand” requests expressed with the complexity and variability of human language, they provide a … The chat-bot to be evaluated in this trial has been specifically designed by experts in …

Social Relation Extraction from Chatbot Conversations: A Shortest Dependency Path Approach
M Glas – SKILL 2019-Studierendenkonferenz Informatik, 2019 – dl.gi.de
… a comparison method for extracting social relations from chatbot conversations … conversations, used within chat messages between people, or humans and chatbots … classifiers, standard classification techniques like Support Vector Machines, logistic regression, decision trees …

Designing an emotionally realistic chatbot framework to enhance its believability with AIML and information states
R Sutoyo, A Chowanda, A Kurniati… – Procedia Computer …, 2019 – Elsevier
… The representation is summed and sent to the multinomial logistic regression classifier for the training process … The participants were suggested to asked the chatbots regarding to FAQs related to their … of this research is to deploy and have an exploration of the chatbot system to …

Survey on Out-Of-Domain Detection for Dialog Systems
YS Jeong, YM Kim – Journal of Convergence for Information …, 2019 – koreascience.or.kr
… needs to intelligent conversational agent, which is also typically called as chatbot or dialog … utterance type, system response, # of words of previous utterance * Method – Logistic regression (LR) for … research direction is to construct a public dataset for the dialog system, and this …

CASA-NLU: Context-Aware Self-Attentive Natural Language Understanding for Task-Oriented Chatbots
A Gupta, P Zhang, G Lalwani, M Diab – arXiv preprint arXiv:1909.08705, 2019 – arxiv.org
CASA-NLU: Context-Aware Self-Attentive Natural Language Understanding for Task-Oriented Chatbots … Natural Language Understanding (NLU) is a core component of dialog systems … handcrafted features and word n-gram based features fed to SVM, logistic regression, etc …

A survey on construction and enhancement methods in service chatbots design
Z Peng, X Ma – CCF Transactions on Pervasive Computing and …, 2019 – Springer
… and one fully connected layer, finally summarizing the decisions with the logistic regression unit … method is still the research hot spot on building customized and context-aware chatbots … we look into the common methods which evaluate the quality of chatbot’s response given …

Resilient chatbots: repair strategy preferences for conversational breakdowns
Z Ashktorab, M Jain, QV Liao, JD Weisz – … of the 2019 CHI Conference on …, 2019 – dl.acm.org
… if a breakdown can be easily repaired, people prefer to resolve it with the chat- bot, whereas if … help users to rephrase; teach user how to interact with the chatbot; proactively making … capabilities; help users to rephrase; teach user how to interact with chatbots; proactively making …

Evaluation and improvement of chatbot text classification data quality using plausible negative examples
K Kuksenok, A Martyniv – arXiv preprint arXiv:1906.01910, 2019 – arxiv.org
… transformation for improved perfor- mance (Arora et al., 2016), and logistic regression with L2 … Commercial chatbot: per- formance evaluation, usability metrics and quality standards of embodied conversational … A quality analy- sis of facebook messenger’s most popular chatbots …

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.1. Logistic Regression (LR) Logistic regression or multinomial logistic regression generalizes to multiclass classification by …

Personalized reason generation for explainable song recommendation
G Zhao, H Fu, R Song, T Sakai, Z Chen, X Xie… – ACM Transactions on …, 2019 – dl.acm.org
… increase in the availability of con- versational data has enabled rapid development of chatbots and dialog … some of these comments are too long or too detailed for a chatbot and should be … We try several popular classifiers, such as logistic regression, decision trees, and SVMs …

Deep learning for spoken dialogue systems: application to nutrition
MB Korpusik – 2019 – dspace.mit.edu
… 31 1.1 Dialogue Systems … 134 7-1 The typical flow of a dialogue system, with spoken language understand- ing followed by dialogue state tracking … The baselines are a lexical matcher (ie, at least two shared words is a match) and logistic regression classifier trained …

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 … The other approaches like SVM, logistic regression all require fixed input size and also results is fixed output size … There are various chatbot or question answering system developed but very few provides correct and efficient answers …

Deep learning based chatbot models
R Csaky – arXiv preprint arXiv:1908.08835, 2019 – arxiv.org
… they are limited to a specific domain, thus users have to be guided by the dialog system towards the task … The second type of dialog agents are the non-task or open-domain chatbots … This means that one should hardly be able to distinguish such a chatbot from a real human, but …

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 user … us to overcome the aforementioned challenge of dialogue coherence in chatbots (see Section … Furthermore, it is sufficiently large for logistic regression analyses (see Section 5 …

Evaluation of Chatbot Prototypes for Taking the Virtual Patient’s History.
A Reiswich, M Haag – dHealth, 2019 – books.google.com
… Naïve Bayes (NB), Linear Support Vector Classification (Linear SVC) and the Logistic Regression (LR) … 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 IEEE …

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 …

Dynamic Search–Optimizing the Game of Information Seeking
Z Tang, GH Yang – arXiv preprint arXiv:1909.12425, 2019 – arxiv.org
… the when, where, and who of the visit; to find a target smart phone, the chatbot may ask … are much less structured, and slot-filling would not be as effective as it is for chatbots … Based on the way in which the dialogue system generates/selects its response, those systems can be …

Computational Investigations of Pragmatic Effects in Natural Language
J Kabbara – Proceedings of the 2019 Conference of the North …, 2019 – aclweb.org
… assistant to carrying out a simple conver- sation with a chatbot to asking … the-art perfor- mance on definiteness prediction, outperforming a previous logistic regression classifier (De … applica- tions in natural language generation tasks such as summarization and dialogue systems …

FinBrain: when finance meets AI 2.0
X Zheng, M Zhu, Q Li, C Chen, Y Tan – Frontiers of Information Technology …, 2019 – Springer
… is the most accurate technique in predicting credit card fraud, followed by GBDT and logistic regression (LR … Generally, chatbot systems can analyze customers’ goals and are highly responsive to cus- tomers with … (2017) presented a task- completion dialogue system to complete …

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 …

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
… 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 to … These statistics are fed into a logistic-regression classifier that decides on whether a triple is …

Survey on evaluation methods for dialogue
JM Deriu, A Rodrigo, A Otegi, E Guillermo, S Rosset… – 2019 – digitalcollection.zhaw.ch
… There are many different approaches to design a dialogue manager, which are partly dictated by the application of the dialogue system. However, there are three broad classes of dialogue systems, which we encounter in the literature: task-oriented systems, conversational …

Pilot Data Collection Survey and Analytical Techniques for Persuasion Engineering Systems
A Braca, B Spillane, V Wade, P Dondio – tara.tcd.ie
… and media strategies, and more recently, through the use of interactive technologies such as chat bots … classes (1-10) instead of 3. In place of a multinomial logistic regression, other algorithms … Research into persuasive dialog systems is impor- tant as it can be used to increase …

Samvaadhana: A Telugu Dialogue System in Hospital Domain
SR Duggenpudi, KSS Varma, R Mamidi – … of the 2nd Workshop on Deep …, 2019 – aclweb.org
… 2019. Spoken dialogue system using recognition of user’s feedback for rhythmic dialogue. Page 8. 241 Metric Description … 2007. Large-scale bayesian logistic regression for text categorization. Technometrics, 49(3):291– 304 … Gotora. 2017. A neural-network based chat bot …

# MeTooMaastricht: Building a chatbot to assist survivors of sexual harassment
T Bauer, E Devrim, M Glazunov, WL Jaramillo… – … Conference on Machine …, 2019 – Springer
… classified as rule-based (scripted) or end-to-end (usually based on deep learning) chatbots … grams and Doc2Vec with Distributed Bag of Words (DBOW) with a Logistic Regression classifier … fellow at Brandeis University, in building the dialogue flow of the chatbot implemented in …

Listening between the lines: Learning personal attributes from conversations
A Tigunova, A Yates, P Mirza, G Weikum – The World Wide Web …, 2019 – dl.acm.org
… then be a distant source of background knowledge for personalization in downstream applications such as Web-based chatbots and agents … General-purpose chatbot-like agents show decent performance in benchmarks (eg, [13, 20, 37]), but critically rely on … Logistic regression …

Situated interaction
D Bohus, E Horvitz – The Handbook of Multimodal-Multisensor Interfaces …, 2019 – dl.acm.org
… at dialog between computers and people were text-based dialog systems, such as Eliza [Weizenbaum 1966], a pattern- matching chat-bot that emulated a … Most work in spoken dialog systems has traditionally focused on dyadic settings, where a dialog system interacts with a …

A comparative study of social bot classification techniques
F Örnbratt, J Isaksson, M Willing – 2019 – diva-portal.org
… Web Robots (crawlers) ? Chatbots (natural language based dialog system) ? Spambots (bots that advertise and post spam on online messaging platforms) … linear regression, logistic regression, naive bayes, k-nearest-neighbour, decision tree and random …

ProductQnA: Answering user questions on e-commerce product pages
A Kulkarni, K Mehta, S Garg, V Bansal… – … Proceedings of The …, 2019 – dl.acm.org
… KEYWORDS question answering; deep learning; chatbot; e-commerce ACM Reference Format: Ashish … and re- cently, automatic question answering [17, 20] and chatbots [22 … Model Architecture Multi class Accuracy AUC (weighted) Logistic Regression -6.5% -3.1% FastText 0.0 …

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
… This suggests that having a spoken dialogue system be continuously polite (as done in … in user utterances can thus help all kinds of dialogue systems better estimate … various machine learning approaches such as Support Vector Machines and Logistic Regression with various …

Question Generation with Adaptive Copying Neural Networks
X Lu – 2019 – curve.carleton.ca
… 23 2.14 An example of dialog system [7]. . . . 24 … people as if they were human. Medical chatbots will soon function as assistants to diagnose patients’ symptoms … its own set of features through learning. In the general Logistic Regression, we were …

Submodular optimization-based diverse paraphrasing and its effectiveness in data augmentation
A Kumar, S Bhattamishra, M Bhandari… – Proceedings of the 2019 …, 2019 – aclweb.org
… and Bilmes, 2011), data selection in machine translation (Kirchhoff and Bilmes, 2014) and goal-oriented chatbot training (Dimovski … works in this area have focused on the task of producing diverse responses in dialog systems (Li et … 1. LogReg: Simple Logistic Regression model …

An Innovative Healthcare Service Providing System
S AV, M KG – 2019 – papers.ssrn.com
… Facebook Messenger, Apple?s Siri, Hike Natasha, Amazon?s Alexaare some of the existing chatbots available … More than the other machine learning algorithms it is found that Logistic Regression has been the best … [1] AnithaRaoGadiyar, “The Chatbot Imperative: Intelligence …

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 …

Unsupervised dialogue intent detection via hierarchical topic model
A Popov, V Bulatov, D Polyudova… – Proceedings of the …, 2019 – aclweb.org
… One of the challenges during a task- oriented chatbot development is the scarce availability of … More universal and robust dialogue systems should work without any supervision or defined rules … Logistic regression on the tf-idf representation is quite a strong algorithm for the text …

Spoken Dialogue Processing for Multimodal Human?Robot Interaction
T Kawahara – 2019 – researchgate.net
… pub/ICMI19?tutorial.pdf 1 Spoken Dialogue Systems (SDS) are prevailing • Smartphone Assistants • Smart Speakers … DOMAIN: weather PLACE: kyoto DAY: saturday ASR engine Architecture of Spoken Dialogue System (SDS) 37 Dialog Management …

My Buddy App: Communications between Smart Devices through Voice Assist
MG Patel, MK Patil – 2019 – academia.edu
… Chatbots are the virtual assistant that programmed for providing automatically answers to the user request. Figure 3 Chatbot flow Page 4 … It provides the interface between the linguistic and logistic regression model and the manual performance …

A Study of State Aliasing in Structured Prediction with RNNs
LE Asri, A Trischler – arXiv preprint arXiv:1906.09310, 2019 – arxiv.org
… Note that we also used REINFORCE to train an agent (referred to as Logistic Regression in the table) that maps the input directly to a … A sequence-to-sequence model for user simulation in spoken dialogue systems … understanding the low-diversity problem of chatbots …

Question generation
C Room – Architecture, 2019 – devopedia.org
… They over-generate questions and then rank them using a logistic regression model. Jul 2010 … For training question answering ( QA ) or dialogue systems, QG can produce question-answer pairs. Chatbots trained on QG can ask relevant questions in an ongoing dialogue …

A comparative study of word embedding methods for early risk prediction on the Internet
E Fano – 2019 – diva-portal.org
… It would be possible to develop chat bots and other dialogue systems that can … Their first and second models consisted of an ensemble of logistic regression classifiers, three of them based on bags of words with different term weightings and the fourth, present only in their …

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

Deep learning for database mapping and asking clarification questions in dialogue systems
M Korpusik, J Glass – IEEE/ACM Transactions on Audio …, 2019 – ieeexplore.ieee.org
… ap- plicable to dialogue systems. Li et al. showed that deep RL models enabled chatbots to generate more diverse, informative, and coherent responses than standard encoder-decoder mod- els [27]. Other work leveraged RL to construct a personalized dialogue system for a …

NLUBroker: a flexible and responsive broker for cloud-based natural language understanding services
L Xu, A Iyengar, W Shi – 11th {USENIX} Workshop on Hot Topics in Cloud …, 2019 – usenix.org
… Dialog sys- tems, especially goal-oriented dialog systems, are now com- monly used to … a user interested in finding the most appropriate service for a chatbot; several arguments can … Both the word embedding model and trained logistic regression model are saved and launched …

A Readiness Evaluation of Applying e-Government in the Society: Shall Citizens begin to Use it?
LT Khrais, MA Mahmoud… – Editorial Preface From …, 2019 – researchgate.net
… A. Chatbots Applications and Uses Artificial dialogue systems are interactive talking machines called chatbots. Chatbot applications have been around for a long time; the first well-known chatbot is Joseph Weizenbaum? s Eliza program developed in the early 1960s …

Introducing MANtIS: a novel multi-domain information seeking dialogues dataset
G Penha, A Balan, C Hauff – arXiv preprint arXiv:1912.04639, 2019 – arxiv.org
… 4 A generic dialogue system is composed of the following: natural language understand- ing … Domain specific dialogue systems do not generalize to new/unseen information needs … following learning algorithms: SVM, AdaBoost, Gradient Boost- ing and Logistic Regression 8. We …

Enabling IoT in Education 4.0 with BioSensors from Wearables and Artificial Intelligence
MI Ciolacu, L Binder, H Popp – 2019 IEEE 25th International …, 2019 – ieeexplore.ieee.org
… The chatbot for mathematics answers the questions with voice output or in writing feedback. In addition to Ciolacu et al … He suggests classification trees and logistic regression that can be easily used for Higher Education regarding accuracy and simplicity of algorithm …

Your instruction may be crisp, but not clear to me!
P Pramanick, C Sarkar… – 2019 28th IEEE …, 2019 – ieeexplore.ieee.org
… A robot deployed in our surrounding can utilize such a chatbot to derive the human intention and … Most of the existing chatbots are trained with query- response pairs and a given query is … corresponding intent Yi, ie D = {xi,yi}N i=1. We use a logistic regression classifier, trained …

Towards Interactive Advisory System for Security Export Control
A Obayashi, R Rzepka23 – researchmap.jp
… We developed an interactive Slack chatbot11 prototype to show the feasibil- ity of the … system’s questions, also research pa- pers can be one sent to the dialog system to provide a … Random 0.10 0.10 Multinomial NB 0.14 0.75 Linear SVC 0.56 0.89 Logistic Regression 0.25 0.86 …

Long Term Memory in Conversational Robots
J Olson, E Södergren – 2019 – diva-portal.org
… A chatbot with a long-term memory is likely to improve customer engagement [3 … The classifier utilizes Logistic Regression to maximize said function, by modifying the parameters of its … by advances in technology, such as automated response systems and chatbots for instance …

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 …

Release strategies and the social impacts of language models
I Solaiman, M Brundage, J Clark, A Askell… – arXiv preprint arXiv …, 2019 – arxiv.org
… tions of chatbots alongside its latest release [19] … harmful outcomes. A canonical example is Microsoft’s “Tay” chatbot, a Twitter bot that replied based on … fake. And we released a simple classifier baseline that trains a logistic regression detector on TF-IDF …

On the Impact of Voice Encoding and Transmission on the Predictions of Speaker Warmth and Attractiveness
LF Gallardo, R Sanchez-Iborra – ACM Transactions on Knowledge …, 2019 – dl.acm.org
… Chatbots are becoming increasingly predominant, especially for customer service and personal companions and … Adaptive human- machine spoken dialog systems are already able to react to … Other classifiers based on k-neighbors and logistic regression procedures were also …

A Question Answering and Quiz Generation Chatbot for Education
AS Sreelakshmi, SB Abhinaya, A Nair… – 2019 Grace Hopper …, 2019 – ieeexplore.ieee.org
… transformations, and then ranking of these generated questions based on logistic regression model based ranker … Chatbots in education: A passing trend or a valuable pedagogical tool … Smart answering Chatbot based on OCR and Overgenerating Transformations and Ranking …

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 …

Structured Knowledge Discovery from Massive Text Corpus
C Zhang – arXiv preprint arXiv:1908.01837, 2019 – arxiv.org
… As voice assistants and chat-bots become more and more popular, users may ask smart devices questions via voice … For example, booking a flight with customer service representatives. Figure 1 illustrates three scenarios on community Q&A, voice assistant/chatbot, and service …

Ambient Assisted Living with Deep Learning
E Merdivan – 2019 – tel.archives-ouvertes.fr
… important components: improving activity recognition, addressing privacy concerns and developing intelligent dialogue systems for AAL systems, with an emphasis on a framework which is flexible and scalable for real-world applications. Page 20. Chapter 1. Introduction 3 …

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 …

Adaptive and Personalized Systems Based on Semantics
P Lops, C Musto, F Narducci, G Semeraro – Semantics in Adaptive and …, 2019 – Springer
… In particular, the impact of the feature generation process on the performance of the system was evaluated by injecting 20, 40, and 60 most related Wikipedia concepts in a content-based recommender based on Logistic Regression …

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 …

Novel Methods for Efficient Dialogue Policy Learning by Improving Agent-User Interaction
B Peng – 2019 – search.proquest.com
… Research and Development of Human Assist AI to Build Chatbot (Journal Paper, work in progress, proposal funded by ITF) ix Page 12 … realize this goal. A spoken dialogue system is a computational … speech, text. Spoken dialogue systems have long been of inter …

Sémantické porozum?ní konverzaci
P Lorenc – 2019 – dspace.cvut.cz
… Usually chatbot gets a query q and system returns a response r. Respond model has usually two options … Translation is another very hot topic following by chatbots … General form looks very similar to logistic regression[29]: P(O|S) = 1 Z(S) n ? i=1 ?(oi,oi?1,S) …

The Impact of Toxic Replies on Twitter Conversations
N Salehabadi – 2019 – rc.library.uta.edu
… Natural Language Processing (NLP) Techniques are used in Question-Answering, Chatbots and dialog systems. Generative models are state of the art for generating text, and … classical methods: (1) feature engineering including Logistic Regression, Bayesian models …

EMMA: An Emotion-Aware Wellbeing Chatbot
A Ghandeharioun, D McDuff… – 2019 8th …, 2019 – ieeexplore.ieee.org
… Synchronous, text-based interventions, either by a human or a chat-bot, have shown … the BL quadrant of Russel’s circumplex model of emotion, the chatbot would recommend … We experimented with a range of classifiers includ- ing Logistic Regression, Ridge, AdaBoost …

Semantic and Discursive Representation for Natural Language Understanding
D Sileo – 2019 – tel.archives-ouvertes.fr
… Under- standing the needs of humans paves the way for their automatic fulfilment (as in chatbot systems, robotics or information retrieval) … erating costs. Some tasks can rely on other tasks; for instance, a chatbot system (1-1c) can be decomposed into modules …

Modeling interaction structure for robot imitation learning of human social behavior
M Doering, DF Glas, H Ishiguro – IEEE Transactions on Human …, 2019 – ieeexplore.ieee.org
… Terms—Human–robot interaction, imitation learning, in- teraction structure, spoken dialog system, unsupervised learning … Frame-based dialog systems keep track of the dialog state by tracking a set … The topic state estimator is a logistic regression classifier that takes an utterance …

Multimodal conversational interaction with robots
G Skantze, J Gustafson, J Beskow – The Handbook of Multimodal …, 2019 – dl.acm.org
… body. Hal only stares at the interlocutor with his (now emblematic) red eye. For a long time, spoken dialogue systems developed in research labs and employed in the industry also lacked any physical embodiment. One reason …

Towards the Learning, Perception, and Effectiveness of Teachable Conversational Agents
N Chhibber – 2019 – uwspace.uwaterloo.ca
… 17 3.3 Conversational Interface . . . . . 19 3.3.1 Why a Conversational Interface? . . . . 19 3.3.2 Dialog System . . . . . 20 3.3.3 Teaching Guidance . . . . . 21 …

Unsupervised Text Representation Learning with Interactive Language
H Cheng – 2019 – digital.lib.washington.edu
… neural-based spoken dialogue systems [36, 37] … Page 24. 13 tion scenario takes place between a human user and a dialogue system powered by conversational … Page 25. 14 (aka chatbots) have been developed for entertainment, companionship and education purpose …

Learning to Converse With Latent Actions
T Zhao – 2019 – lti.cs.cmu.edu
… 2.1 Dialog system pipeline for task-oriented dialog systems . . . . . 8 … These unique features make latent action E2E dialog system powerful and practical for creating dialog systems in a variety of usage and domains. 1.2 Thesis Statement …

Learning to merge-language and vision: A deep evaluation of the encoder, the role of the two modalities, the role of the training task.
R Shekhar – 2019 – eprints-phd.biblio.unitn.it
… by the encoder as general purposed representations. We have proposed and an- alyzed a cognitive plausible architecture in which dialogue system modules are connected through a common grounded dialogue state encoder. Our in-depth …

Evaluation of Methods for Data-Driven Tools that Empower Mental Health Professionals
OA Demasi – 2019 – escholarship.org
… Novice counselors are unable to assume full responsibility for a crisis situation until they have some experience. Some organizations are considering the use of automated interactive agents (chatbots) to replace human counselors …

Artificial Intelligence in Education: 20th International Conference, AIED 2019, Chicago, IL, USA, June 25-29, 2019, Proceedings
S Isotani, E Millán, A Ogan, P Hastings, B McLaren… – 2019 – books.google.com
Page 1. Seiji Isotani· Eva Millán · Amy Ogan · Peter Hastings· Bruce McLaren · Rose Luckin (Eds.) Artificial Intelligence in Education 20th International Conference, AIED 2019 Chicago, IL, USA, June 25–29, 2019 Proceedings, Part I 123 Page 2 …

The adoption of artificial intelligence by South African banking firms: a Technology, Organisation and Environment (TOE) framework
C Mariemuthu – wiredspace.wits.ac.za
… 22 Figure 2.6: Chatbot architecture … These applications of AI can benefit banks in several ways to enhance banking products, improve transaction security and real-time fraud detection, and introduce chatbots for augmented customer service (Gartner, 2017) …

A multimodal approach to sarcasm detection on social media
D Das – 2019 – researchgate.net
… Page 90 8.1 Sample positive and negative reviews, and replies from chatbot-based auto-replier sys- tem. Page 94 … and topics. They propose a logistic regression and a support vector machine (SVM) based super- vised classification algorithm to detect sarcasm …

Multimodal integration for interactive conversational systems
M Johnston – The Handbook of Multimodal-Multisensor Interfaces …, 2019 – dl.acm.org
Page 1. IPART MULTIMODAL LANGUAGE AND DIALOGUE PROCESSING Page 2. Page 3. 1Multimodal Integration for Interactive Conversational Systems Michael Johnston 1.1 Introduction This chapter discusses the challenges …

Artificial Intelligence in Education
S Isotani, E Millán, A Ogan, P Hastings, B McLaren… – 2019 – Springer
Page 1. Seiji Isotani · Eva Millán · Amy Ogan · Peter Hastings · Bruce McLaren · Rose Luckin (Eds.) 123 LNAI 11626 20th International Conference, AIED 2019 Chicago, IL, USA, June 25-29, 2019 Proceedings, Part II Artificial Intelligence in Education Page 2 …

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 …

Response Retrieval in Information-seeking Conversations
L Yang – 2019 – scholarworks.umass.edu
Page 1. University of Massachusetts Amherst ScholarWorks@UMass Amherst Doctoral Dissertations Dissertations and Theses 2019 Response Retrieval in Information-seeking Conversations Liu Yang College of Information and Computer Sciences, UMass Amherst …

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