Machine Learning & Chatbots 2015


Wikipedia:

References:

See also:

100 Best Azure Machine Learning Videos100 Best GitHub: Machine Learning100 Best Machine Learning Lecture Videos100 Best Machine Learning Tutorial VideosMachine Learning & Dialog SystemsMachine Learning & Question Generation 2015Machine Learning as a Service (MLaaS)Machine Learning Meta Guide


Reverse engineering socialbot infiltration strategies in twitter C Freitas, F Benevenuto, S Ghosh… – Proceedings of the 2015 …, 2015 – dl.acm.org … cally posting news or change a template on Wikipedia of all pages in a category [1]. There are companies that develop chatbots for those … content posted by certain types of social bots and humans, and created a tool that incorporated their findings into a machine learning model. … Cited by 21 Related articles All 13 versions

Real conversations with artificial intelligence: A comparison between human–human online conversations and human–chatbot conversations J Hill, WR Ford, IG Farreras – Computers in Human Behavior, 2015 – Elsevier … To our knowledge, however, no research has investigated the linguistic characteristics of a different form of CMC: chatbot communication. Chatbots, or chatterbots, are another widespread domain of CMC. Chatbots are “machine … Cited by 5 Related articles All 7 versions

ALICE chatbot: trials and outputs B AbuShawar, E Atwell – Computación y Sistemas, 2015 – cys.cic.ipn.mx … for developing new ALICE language models, to chat around a specific topic: the techniques involve machine learning from a training corpus; the resulting chatbot chats in … of learning to chat using variety corpora is illustrated in Section 4. Overall outputs, chatbots’ benefits and … Cited by 1 Related articles All 2 versions

Pharmabot: a pediatric generic medicine consultant chatbot BEV Comendador, BMB Francisco… – Journal of Automation …, 2015 – joace.org … [1] “A related term to machine conversation is the chatbot, a conversational … Different chatbots or human-computer dialogue systems have been developed using text communication starting from … [3] “With the improvement of data-mining and machine-learning techniques, better … Cited by 1 Related articles

A chatbot as a Question Answering Tool B AbuShawar, E Atwell – urst.org … which can chat around a specific topic: these techniques involve machine learning from a training corpus of dialogue transcripts, so the resulting chatbot chats in the style of the training corpus [2], [3], [4], [5], [7]. For example, we have a range of different chatbots trained to chat … Related articles

Intelligent Chat Bot for Banking System MA Dole, MH Sansare, MR Harekar, MS Athalye – ijettcs.org … With the improvement of data-mining and machine-learning techniques, better decision-making capabilities, availability of corpora … II. PROPOSED SYSTEM A chat bot for bank system is a computer program designed to simulate an intelligent … Figure 1: Architecture of AI Chatbot … Related articles

Approaches to Measuring the Intelligence of Machines by Quantifying them P Kapoor – ijarcce.com … in the field of machine learning, computer gaming and artificial intelligence), the term„Machine Learning? is defined … making it a test of humanness rather than intelligence.[2] The chatbots have not … For example, if asked “Do you like Microsoft or Apple?” the chatbot would reply, “I … Related articles All 2 versions

Statistical Response Method and Learning Data Acquisition using Gamified Crowdsourcing for a Non-task-oriented Dialogue Agent Y Enokibori, K Takahashi, K Mase – … 2014, Angers, France, March 6-8, …, 2015 – Springer … Keywords: Dialogue agent· Chatbots· Crowdsourcing· Gamification. … ranks previously prepared candidate utterances in order of suitability to the context by the application of a machine learning algorithm. … Parsing the Turing, Test (2009) 6. Worswick, S.: Mitsuku Chatbot (2013). … Related articles All 2 versions

A survey of user classification in social networks G Bai, L Liu, B Sun, J Fang – Software Engineering and Service …, 2015 – ieeexplore.ieee.org … In this section, we present the methods based on non-machine learning in user classification … and MengjunXie propose an entropy-based classification method to identify the chat bot in Yahoo … For Chat Bots, there are two respective trigger mechanism, one is based on the time of … Related articles

A Personal Conversational Model LL Murata, AM Istrate – pdfs.semanticscholar.org … In some sense, telling the system information is like machine learning, but it feels like a … Test (GCT) The traditional, well-renowned qualitative metric for testing a chatbot is the … compared the results among three major categories of objects: available chatbots, different classifiers … Related articles All 4 versions

Answer sequence learning with neural networks for answer selection in community question answering X Zhou, B Hu, Q Chen, B Tang, X Wang – arXiv preprint arXiv:1506.06490, 2015 – arxiv.org … 2 Related Work Prior studies on answer selection generally treated this challenge as a classification problem via em- ploying machine learning methods, which rely on exploring various features to represent QA pair. … Extracting chatbot knowledge from online discussion forums. … Cited by 12 Related articles All 9 versions

The Winograd Schema Challenge: Evaluating Progress in Commonsense Reasoning. L Morgenstern, C Ortiz – AAAI, 2015 – pdfs.semanticscholar.org … Test, including win- ners of the Loebener competition (Christian 2011) and the chatbot Eugene Goostman … Chatbots get away with evading questions that they can’t answer; such … the type of system- atic progress found in other communities, such as machine learning or textual … Related articles All 3 versions

Noun phrases extraction using shallow parsing with C4. 5 decision tree algorithm for Indonesian Language ontology building J Santoso, HV Gani, EM Yuniarno… – 2015 15th …, 2015 – ieeexplore.ieee.org … Ontology plays an important role in some research in Natural Language Processing, such as chatbot in [1] and question answering in … employ transformation-based algorithm to determine a noun phrase chunk which is described as the pioneer of machine learning approach in … Related articles

Machine-Learned Ranking Based Non-Task-Oriented Dialogue Agent Using Twitter Data M Koshinda, M Inaba… – 2015 IEEE/WIC/ACM …, 2015 – ieeexplore.ieee.org … [7] J. Huang, M. Zhou, and D. Yang, ”Extracting Chatbot Knowledge from … [12] Z. Cao, T. Qin, TY Liu, MF Tsai, and H. Li, ”Learning to rank: From Pairwise Approach to Listwise Approach,” Proceedings of the 24th International Conference on Machine Learning(ICML2007), pp. … Cited by 2 Related articles

Introduction to Intellectual Conversational Agents K Panesar – Epicurious, 2015 – bradfordcollege.ac.uk … Rudowsky (2004) writes that between 1960s and 1990s, substantial progress were made in the sub-areas of AI, such as knowledge representation and inference, machine learning, vision and robotics. … chatbots. org/chatbot/alice/>[Accessed 5th July 2014]. … Related articles All 2 versions

Artificial Intelligence: Science and Impact MSP Miller – 2015 – academia.edu … Micro worlds 1980s Rule Based Expert Systems (Symbolic) 1990s AI Winter 2010s Machine Learning (Statistical) Algorithms that learn from raw data 2012+ Deep Learning … Chef Case Based Planner Cleverbot Case based Chatbot Cyc Commonsense Reasoning Daydreamer … Related articles

The ubuntu dialogue corpus: A large dataset for research in unstructured multi-turn dialogue systems R Lowe, N Pow, I Serban, J Pineau – arXiv preprint arXiv:1506.08909, 2015 – arxiv.org … subfields of AI— computer vision, speech recognition, machine translation—fundamental break-throughs were achieved in recent years using machine learning … conversations with several turns (sig- nificantly more than 3). • Task-specific domain, as opposed to chatbot systems. … Cited by 25 Related articles All 12 versions

OMG UR Funny! Computer-Aided Humor with an Application to Chat M Wen, N Baym, O Tamuz, J Teevan… – … of the Sixth …, 2015 – computationalcreativity.net … References Augello, A., Saccone, G., Gaglio, S., and Pilato, G. 2008. Humorist bot: Bringing computational humour in a chat-bot system. … R-max: a general polynomial time algorithm for near-optimal reinforcement learning. Journal of Machine Learning Research, 3:213– 231. … Cited by 3 Related articles All 14 versions

Hierarchical neural network generative models for movie dialogues IV Serban, A Sordoni, Y Bengio, A Courville… – arXiv preprint arXiv: …, 2015 – arxiv.org Page 1. arXiv:1507.04808v1 [cs.CL] 17 Jul 2015 Hierarchical Neural Network Generative Models for Movie Dialogues Iulian V. Serban1, Alessandro Sordoni1, Yoshua Bengio1,3, Aaron Courville1 and Joelle Pineau2 1Department … Cited by 16 Related articles All 4 versions

AIML Based Voice Enabled Artificial Intelligent Chatterbot I Ahmed, S Singh – International Journal of u-and e-Service, …, 2015 – researchgate.net … Technologies. Pp.89-96, ACL(2007). [7] Abu Shawer B. and Atwal A. Machine Learning from dialogue corpora to generate chatbots. Expert Update journal, Vol. 6, No 3, pp 25-30 (2003). [8] Steven Birds, Ewan Klein and Edward Lapper. … Cited by 1 Related articles All 3 versions

Example-based dialog modeling for a mobile system T Cunha – researchgate.net … are the steps followed for the construction of the classifier: Definition of domains, Definition of the features and Definition of the machine learning algorithm. … of this kind of semantic network for the Portuguese language cripple the use of this approach with our Chatbot application. … Related articles

Advances in natural language processing J Hirschberg, CD Manning – Science, 2015 – science.sciencemag.org … power, (ii) the availability of very large amounts of linguistic data, (iii) the development of highly successful machine learning (ML) methods … Chatbots following in the tradition of ELIZA (21) handle open-domain interaction by cleverly repeating variations of the human input; this … Cited by 30 Related articles All 9 versions

A Review of Semantic Search Methods to Retrieve Information from the Qur’an Corpus MMA Alqahtani, E Atwell – 2015 – eprints.whiterose.ac.uk … MRes thesis, University of Leeds. Abu Shawar, B. and Atwell, E. 2004. An Arabic chatbot giving answers from the Qur’an. Proceedings of TALN. … Dukes, K. 2013. Statistical parsing by machine learning from a classical Arabic treebank. PhD thesis. Explorer, Q. 2005. … Related articles

Teenchat: a chatterbot system for sensing and releasing adolescents’ stress J Huang, Q Li, Y Xue, T Cheng, S Xu, J Jia… – … Conference on Health …, 2015 – Springer … Inheriting the mechanism of ELIZA, another famous chatbot ALICE [34] engaged in a … [32,40] regarded emotion recognition as a classification problem, and used machine learning methods to … Kerly, A., Hall, P., Bull, S.: Bringing chatbots into education: Towards natural language … Cited by 3 Related articles All 3 versions

Conversational Agent that Models a Historical Personality A Bogatu, D Rotarescu, T Rebedea, S Ruseti – rochi.utcluj.ro … like IBM’s Watson, which uses Natural Language Processing (NLP), information retrieval, machine learning and other … The advantage of implementing a chat-bot that answers trivia questions from the … M. Procter, and D. Mah, ?Freudbot: An investigation of chatbot technology in … Related articles

ICRC-HIT: A Deep Learning based Comment Sequence Labeling System for Answer Selection Challenge XZBHJ Lin, YXX Wang – SemEval-2015, 2015 – aclweb.org … 2013. Jizhou Huang, Ming Zhou, and Dan Yang. 2007. Extracting chatbot knowledge from online discussion forums. … In Proceedings of the 29th International Conference on Machine Learning (ICML), Edinburgh, Scotland, UK. 2012. 214 Cited by 4 Related articles All 10 versions

Computational Notebooks for AI Education. KJ O’Hara, DS Blank, JB Marshall – FLAIRS Conference, 2015 – researchgate.net … Because Machine Learning (ML) is heavily based on statis- tics and many statisticians have already adopted notebook- based computing, many ML examples are widely available (see … Other non-robotics assignments included an Eliza-based chatbot and a graphical avatar. … Cited by 3 Related articles All 8 versions

Cognitive science in telemedicine: from psychology to artificial intelligence G Pravettoni, R Folgieri, C Lucchiari – Tele-oncology, 2015 – Springer … artificial intelligence systems such as the artificial neural networks, but also the machine learning algorithms, is … Chatbots are, in this sense, a powerful, easy-to-use and well-known app allowing … The introduction of the chatbot in the application could be the key to experiment new … Cited by 1 Related articles All 3 versions

TeenChat: A Chatterbot System for Sensing and Releasing Adolescents’ Stress J Jia, L Feng – … Science: 4th International Conference, HIS 2015, …, 2015 – books.google.com … Inheriting the mechanism of ELIZA, another famous chatbot ALICE [34] engaged in a conversation … 40] regarded emotion recognition as a classification problem, and used machine learning methods to … 426–435 (2003) Kerly, A., Hall, P., Bull, S.: Bringing chatbots into education … Related articles

ELIZA fifty years later: An automatic therapist using bottom-up and top-down approaches R Rzepka, K Araki – Machine Medical Ethics, 2015 – Springer … 4.3 Chatbot for Discovering Abnormalities. … In normal circumstances, machine learning techniques would help to automatically set such a threshold by receiving feedback, but when the user’s health is at stake, this approach can be unethical. 6 Conclusions. … Cited by 2 Related articles All 8 versions

Imitation Technology A Gupta, G Grand – 2015 – gabegrand.com … We found that using machine learning techniques to build caricatures of people or organizations provides … Some of the earliest research in the field of AI concerns chatbots that were … In the early 1960s, MIT computer scientist Joseph Weizenbaum created a chatbot called ELIZA …

Adopting Semantic Similarity for Utterance Candidates Discovery from Human-to-Human Dialogue Corpus RY Shtykh, M Makita – International Workshop on Future and Emergent …, 2015 – Springer … submitted to the system, and candidate utterances (potential responses from the chat bot) sampled from … 2007). 4. Wu, Y., Wang, G., Li, W., Li, Z.: Automatic chatbot knowledge acquisition … In: Proceedings of the 31st International Conference on Machine Learning (ICML-2014), pp. … Related articles All 4 versions

Using Vector Space Model in Question Answering System A Hartawan, D Suhartono – Procedia Computer Science, 2015 – Elsevier … [1]; James Pustejovsky and Amber Stubbs. Natural Language Annotation for Machine Learning. Beijing: O’Reilly. … Using Dialogue Corpora to Train a Chatbot. In: Archer, D., Rayson, P., Wilson, A., McEnery, T. (eds.) Proceedings of the Corpus Linguistics 2003 Conference, pp. … Related articles All 2 versions

An Introduction to Artificial Intelligence in Behavioral and Mental Health Care DD Luxton – Artificial Intelligence in Behavioral and Mental …, 2015 – books.google.com … Machine Learning and Artificial Neural Networks Machine learning (ML) is a core branch of AI that aims to give compu- ters the ability to learn … used in these systems were later adapted for use in the simple precursors of today’s virtual agents, known as “chatbots” or “chatterbots … Related articles

A Review of Semantic Search Methods to Retrieve Information from the Qur’an Corpus E Atwell – Technology – researchgate.net … MRes thesis, University of Leeds. Abu Shawar, B. and Atwell, E. 2004. An Arabic chatbot giving answers from the Qur’an. Proceedings of TALN. … Dukes, K. 2013. Statistical parsing by machine learning from a classical Arabic treebank. PhD thesis. Explorer, Q. 2005. … Related articles All 2 versions

A personal agents hybrid architecture for question answering featuring social dialog M Coronado, CA Iglesias… – Innovations in Intelligent …, 2015 – ieeexplore.ieee.org … We took this approach instead of using a machine learning implementation (eg a Support Vector Machine) because hav- ing ChatScript already in the system made it easier, and the precision in this usecase was of 83 … [6] A. Kerly, P. Hall, and S. Bull, “Bringing chatbots into educa … Related articles

A chatbot service for use in video game development AJ Larsen – 2015 – 146.141.12.21 … The problem with chatbots is that they require a lot of work to develop as can … stock responses of single chatbot to convey different NPC personas. Surveys were … Statistical methods use machine learning techniques with a large set of annotated … Related articles All 2 versions

Remote Virtual Assistant Using Whatsapp NS Hinge, SM Talekar, PP Hande… – i-manager’s Journal …, 2015 – search.proquest.com … Natural Language Processing Application for Android. [2]. Abu Shawer B. and Atwal A., (2014). Machine Learning from dialogue corpora to generate chatbots. Expert Update Journal. Vol.6, No.3, pp.25-30. [3]. Wallace, R., Tomabachi, H., and Aimles, D. (2003). …

Artificial intelligence in process of collecting and analyzing data within police works K Kuk – Nauka, bezbednost, policija, 2015 – scindeks.ceon.rs … 2 S. Russell, P. Norvig, Artificial Intelligence: A Modern Approach, Prentice-Hall, 2010. 3 TM Mitchell, Machine Learning, McGraw-Hill, Inc., New York, USA, 1997. … neprijatelja. Postoji više vrsta botova, a najpoznatijih od njih su: Spambot, Chatbot i Web crawling bot. … Related articles All 2 versions

Making Sense of Large-Group Discussion Using Automatically Generated RST-Based Explanations ACB Garcia, M Klein – Available at SSRN 2554838, 2015 – papers.ssrn.com … pro or cons. Carvalho and Cohen [4] present a similar SA classification method, but for processing emails. Soller and Lesgold [31] proposed a machine learning technique for classifying the posts. Consequently, we can assume … Related articles

A proposal for the development of adaptive spoken interfaces to access the Web D Griol, JM Molina, Z Callejas – Neurocomputing, 2015 – Elsevier … Besides spoken and written language have become popular with the incorporation of chatbots for web-based customer support [29 … The most widespread methodology for machine-learning of dialog strategies consists of modeling human–computer interaction as an optimization … Cited by 1 Related articles All 3 versions

Digital Disruption at Work CB Frey, T Berger – Digital Opportunities – digitaliseringskommissionen.se … 17 Above all, Machine Learning allows computers to “learn” without explicit programmed instructions, allowing them to improve over time. … Lastly, strides were being made in replicating human social intelligence last year when a chat bot for the first time passed the ‘Turing test … Related articles

Guide to chat apps T Barot, E Oren – Tow Center for Digital Journalism, 2015 – cjr.org … Other companies like IBM, a pioneer in machine learning that introduced the Watson system, may … Facebook, too, recently launched a beta of a personal chatbot assistant named M, which … that publishers like The Washington Post are already deploying simple chatbots on apps … Cited by 1

Real-Time Topic and Sentiment Analysis in Human-Robot Conversation E Russell – 2015 – epublications.marquette.edu … Due to these restrictions, rule-based reply methods such as those used in chatbots are avoided, as are domain-specific sentiment analysis classifiers and any … utterances using natural language processing and often machine learning techniques [9, 10]. … Related articles All 2 versions

Information Retrieval in Wikipedia with Conceptual Directions J Szyma?ski – … Conference on Distributed Computing and Internet …, 2015 – Springer … Cognitive Sys- tems Research 14, 84–100 (2012) 17. Shawar, B., Atwell, E.: Chatbots: are they really useful? Zeitschrift für Computerlinguistik und Sprachtechnologie, 29 (2007) 18. … Quinlan, J.: Induction of decision trees. Machine Learning 1, 81–106 (1986) 21. … Related articles All 3 versions

Learning Inference by Induction C Sakama, T Ribeiro, K Inoue – International Conference on Inductive …, 2015 – Springer … An interesting question is whether a machine learning algorithm can discover a new axiomatic system that is semantically equivalent to \(\mathcal{L}\). It … If one develops an AI that learns and understands conversational implicature, it will realize an intelligent chat bot that can …

Library3.0 for Public Library HCY Chan – Journal of Service Science and Management, 2015 – search.proquest.com … This generally involves the application of Machine Learning (ML) techniques, whose goal is learning to categorize new information items based on previously seen information (Lops et al., 2011) [37]. … Chatbots can even interact with users through intelligent conversation. … Cited by 1 Related articles All 8 versions

Analyzing Online Voting Systems for Flaw Detection MS Rahim, E Chowdhury – 2015 – content.grin.com … engine. Other examples include the original Internet relay chat bots and chatterbots. A feed bot … cessing: Deep neural networks with multitask learning.”Proceedings of the 25th interna- tional conference on Machine learning. ACM, 2008. [28] Nixon, Mark. … Related articles All 2 versions

Categories for paper T Matsuda – adada.info … box. KOTOBA JAM, originally a chat-bot system, generates completely unexpected neologisms by combining keywords of the discussed subject with randomly picked modifiers from various designed-modifier selections. The … Related articles

Wizard of Oz experimentation for language technology applications: Challenges and tools S Schlögl, G Doherty, S Luz – Interacting with Computers, 2015 – iwc.oxfordjournals.org … categories. In the first category, we find dialogue management (DM) tools which focus on the evaluation of language technology components and whose primary application lies in the area of NLP and machine learning. Tools … Cited by 6 Related articles All 6 versions

Analysis of types of self-improving software RV Yampolskiy – International Conference on Artificial General …, 2015 – Springer … Machine Learning 28(1), 105–130 (1997) 46. Schmidhuber, J.: A general method for incremental self-improvement and multiagent learning. … Ali, N., Schaeffer, D., Yampolskiy, RV: Linguistic profiling and behavioral drift in chat bots. … Cited by 7 Related articles All 5 versions

Bridging gaps between planning and open-domain spoken dialogues K Jokinen – Language Production, Cognition, and the Lexicon, 2015 – Springer … Although the chatbot applications may sound fairly free and natural, they still require manually built domain models and … Open-domain QA systems use sophisticated machine-learning techniques, question classifiers, search engines, ontologies, summarization, and answer … Cited by 1 Related articles All 3 versions

Davidson’S Test D Davidson’s – 2015 – mrloh.se … Recent winners of the Loebner Prize (AISB 2015), which is awarded to the most human-like chatbot judged by a Turing … Turing’s wrong prediction of the development can be mainly accredited to his underestimation of the required processing power for Machine Learning (1950, p … Related articles

Question Generation from Knowledge Graphs D Seyler, K Berberich, G Weikum – 2015 – pubman.mpdl.mpg.de … 11 2.3 Machine Learning . . . . . … background on knowledge bases and the Semantic Web. Moreover, we give a short introduction to machine learning and regression problems. We close the background chapter with a discussion about techniques to process large datasets. … Related articles

Cognitive computing, analytics, and personalization S Earley – IT Professional, 2015 – ieeexplore.ieee.org … In fact, there are numer- ous chat bots that act as intelli- gent agents for customer service requests and are used to augment call centers and customer help … natural language processing, in- formation retrieval, knowledge representation and reasoning, and machine learning). … Cited by 1 Related articles All 3 versions

Towards a Persuasive Dialog System Supporting Personal Health Management V Götzmann – 2015 – isl.anthropomatik.kit.edu … alleviate this, other approaches discard of the notion of manually designed rules and deploy machine learning instead … Another much researched domain are chatbots. … When thinking of how a chatbot might produce interesting conversations, the idea to use external datasources … Related articles

Laughing With A Virtual Agent: An Evaluation Study Using A Virtual Character Expressing Different Copying Behaviours. M Poesio, B Biancardi, C Pelachaud – perso.telecom-paristech.fr … 29 2 Virtual Agents 33 2.1 Definition and types of virtual agents . . . . . 33 2.1.1 Embodied Conversational Agents . . . . . 33 2.1.2 Chatbots . . . . . 37 2.1.3 Avatars . . . . . … Related articles

[BOOK] Artificial Superintelligence: A Futuristic Approach RV Yampolskiy – 2015 – books.google.com … 2014 Chatbot convinced 33% of the judges, in a restricted version of a Turing test, that it was human and by doing so passed. From these examples, it is easy to see that not only is progress in AI taking place, but also it is actually accelerating as the technology feeds on itself. … Cited by 9 Related articles All 2 versions

Dancing with Physio: A Mobile Game with Physiologically Aware Virtual Humans J Arroyo-Palacios, M Slater – ieeexplore.ieee.org Page 1. 1949-3045 (c) 2015 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This … Related articles All 2 versions

User Information Extraction for Personalized Dialogue Systems T Hirano, N Kobayashi, R Higashinaka, T Makino… – SEMDIAL 2015 …, 2015 – flov.gu.se … Chat bot systems such as ELIZA (Weizenbaum, 1966) and ALICE (Wallace, 2004) extract the user information, name, and hobby of the user by using predefined pattern rules to … In Proceedings of the Eighteenth In- ternational Conference on Machine Learning, pages 282–289. … Related articles All 5 versions

Social Media Analytics of Smoking Cessation Intervention: User Behavior Analysis, Classification, and Prediction M Zhang – 2015 – idea.library.drexel.edu … users to find proper topics or peers to discuss or interact with. It would be helpful if we could apply machine learning techniques to understand user generated information in online health communities, and recommend discussion topics to users to participate in. … Related articles All 2 versions

Social talk capabilities for dialogue systems T Klüwer – 2015 – universaar.uni-saarland.de … often realized by integrating a chatbot. However, the integration of a chatbot can only be seen as a quick-and-dirty solution. Chatbots are separate components with nearly no intelligence. The integration of a traditional surface … Cited by 1 Related articles All 3 versions

[BOOK] Calm Technology: Principles and Patterns for Non-intrusive Design A Case – 2015 – books.google.com Page 1. Amber Case Calm NON-INTRUSIVE DESIGN PRINCIPLES AND PATTERNS FOR Technology Page 2. ORELLY Calm Technology How Can you design technology that becomes a “Too often, our part of a user’s life and not a distraction from it? … Cited by 2 All 2 versions

[BOOK] Apache Solr D Shahi – 2015 – Springer Page 1. Shahi Apache Solr Apache Solr A Practical Approach to Enterprise Search — Dikshant Shahi THE EXPERT S VOICE® IN ENTERPRISE SEARCH Page 2. Apache Solr A Practical Approach to Enterprise Search Dikshant Shahi Page 3. … Cited by 1 All 4 versions

Sentence extraction with topic modeling for question–answer pair generation CH Wu, CH Liu, PH Su – Soft Computing, 2015 – Springer … In: Proceedings of the 23rd international conference on machine learning. … In: Proceedings of QG2010: the third workshop on question generation; Shawar BA, Atwell E (2007) Different measurements metrics to evaluate a chatbot system. … Cited by 1 Related articles All 3 versions

A minimal architecture for general cognition MS Gashler, Z Kindle, MR Smith – 2015 International Joint …, 2015 – ieeexplore.ieee.org … Babysitting Research Politics Dating Cooking Driving cars Chat bots long-term planning RTS games Robot vacuumsEquation solving Maze-running Chess Fig. 1. A subjective plot of several cognitive challenges. Advances in machine learning, especially with deep artifical … Related articles All 6 versions

Game AI Appreciation, Revisited M Lewis, K Dill – Game AI Pro 2: Collected Wisdom of Game AI …, 2015 – books.google.com … Much like with machine learning, there is a fundamental tension with the desire for authorial control, but still some signifi- cant potential. … Even widely celebrated “chat bots” in the spirit of ELIZA [Weizenbaum 66] can be confounded or otherwise reveal their artificiality within the … Cited by 2 Related articles

[BOOK] Speech and Language Technology for Language Disorders K Beals, D Dahl, R Fink, M Linebarger – 2015 – books.google.com Page 1. Katharine Beals, Deborah Dahl, Ruth Fink and Marcia Linebarger Speech and Language Technology for Language Disorders Page 2. Speech Technology and Text Mining in Medicine and Health Care Series Editor … Related articles All 2 versions

Artificial Intelligence Techniques in Human Resource Management—A Conceptual Exploration S Strohmeier, F Piazza – Intelligent Techniques in Engineering …, 2015 – Springer … Knowledge discovery (also “machine learning”, “pattern recognition” or “data mining ”) refers to the process of identifying novel, potentially useful and valid … in web-based ESS, for instance, for speech-based search of content on an HR portal or for realizing chat-bots that answer … Cited by 5 Related articles All 3 versions

The Android and our Cyborg Selves: What Androids Will Teach us about Being (Post) Human AM Bodley – 2015 – research.libraries.wsu.edu Page 1. THE ANDROID AND OUR CYBORG SELVES: WHAT ANDROIDS WILL TEACH US ABOUT BEING (POST)HUMAN By ANTONIE MARIE BODLEY A dissertation submitted in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHHY … Related articles All 5 versions

From Seed AI to Technological Singularity via Recursively Self-Improving Software RV Yampolskiy – arXiv preprint arXiv:1502.06512, 2015 – arxiv.org … Metareasoning, metalearning, learning to learn, and lifelong learning are terms which are often used in the machine learning literature to indicate self-modifying learning algorithms or the process of selecting an algorithm which will perform best in a particular problem domain … Related articles All 5 versions

The humor continuum: From text to smart environments (keynote paper) A Nijholt – Informatics, Electronics & Vision (ICIEV), 2015 …, 2015 – ieeexplore.ieee.org … AI offered general methods for knowledge representation, reasoning and machine learning; CL added more detailed … In contrast, in [13] the ALICE chatbot has been extended with a … The chatbots’ talking head presents its visual feedback using corresponding lip movements and … Cited by 3 Related articles All 7 versions

Technological Moral Proxies and the Ethical Limits of Automating Decision-Making In Robotics and Artificial Intelligence J Millar – 2015 – qspace.library.queensu.ca … 10 For those readers who have not interacted with Apple’s Siri, or a similar chatbot or “artificial agent” technology, I would encourage them to do so and notice the ease with which one is compelled to interact conversationally with it despite the often lackluster results of those … Cited by 1 Related articles All 2 versions

Expert Finding System using Latent Effort Ranking in Academic Social Networks SK Rani, K Raju, VV Kumari – 2015 – mecs-press.com … Clustering Cross Validation Decision Trees Entropy Error Rate Expert System Data Analysis Field Fuzzy Logic Genetic algorithm Gini Index Hypothesis Intelligent Agent KDD Knowledge Discovery Lift Machine Learning Model Nearest … chat bot Cobot computational linguistics … Related articles All 3 versions

“C’Mon dude!”: Users adapt their behaviour to a robotic agent with an attention model L Cavedon, C Kroos, D Herath, D Burnham… – International Journal of …, 2015 – Elsevier … In the simple configuration used here, speech recognition and speech-synthesis—using off-the-shelf components (eg, Dragon Naturally Speaking)—facilitate basic spoken interaction; dialogue management is implemented by a chatbot architecture enhanced with task-specific … Cited by 4 Related articles All 6 versions

Automatic language identification for metadata records: Measuring the effectiveness of various approaches RC Knudson – 2015 – digital.library.unt.edu … They found that a simple naïve Bayes classifier using character and word N-gram features yielded the best performance, with an average accuracy of 87.5% over the six tasks. Automatic language identification is a supervised machine learning algorithm that assigns a text … Related articles All 2 versions

[BOOK] Raspberry Pi for secret agents S Sjogelid – 2015 – books.google.com … She has experience in many diverse areas of engineering-signal processing, machine learning, embedded systems, and web and mobile development … Port tunneling in Windows 125 Port tunneling in Linux or Mac OS X 127 Creating a diversion using a chat bot 128 Introducing … Cited by 7 Related articles All 11 versions

Can You Trust Online Ratings? A Mutual Reinforcement Model for Trustworthy Online Rating Systems HK Oh, SW Kim, S Park, M Zhou – IEEE Transactions on …, 2015 – ieeexplore.ieee.org … Third, we have verified the superiority of TRUE-REPUTATION by comparing it with machine-learning- based algorithms through extensive experiments. … Furthermore, TRUE-REPUTATION, a graph-based algorithm, does not require machine-learning and thus … Cited by 2 Related articles All 3 versions