WEKA & Dialog Systems 2014


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Adapting to personality over time: Examining the effectiveness of dialogue policy progressions in task-oriented interaction AK Vail, KE Boyer – Proceedings of the 15th Annual SIGDIAL …, 2014 – anthology.aclweb.org … der consideration in this study were adminis- tered a Big Five Inventory survey, a type of self- assessment of personality, prior to any interac- tion with the tutorial dialogue system. … The automated classifier was trained using the WEKA machine learning software (Hall et al., 2009). … Cited by 8 Related articles All 9 versions

Analysis of significant dialog events in realistic human–computer interaction D Prylipko, D Rösner, I Siegert, S Günther… – Journal on Multimodal …, 2014 – Springer … 3 Interaction styles and discourse structures Edlund et al. [10] suggest to investigate which metaphors users employ in interacting with a spoken dialog system. … We employed the algorithm imple- mentations from the Weka tool [13]. 4.2.1 Feature set … Cited by 9 Related articles All 3 versions

A clustering approach to assess real user profiles in spoken dialogue systems Z Callejas, D Griol, KP Engelbrecht… – Natural interaction with …, 2014 – Springer … 29 A Clustering Approach to Assess Real User Profiles in Spoken Dialogue Systems … the experiments we employed the X-means clustering algorithm, an extended version of k-means which efficiently estimates the number of clusters to be used [8]. Using the Weka software, we … Cited by 2 Related articles All 5 versions

Data-driven models for timing feedback responses in a Map Task dialogue system R Meena, G Skantze, J Gustafson – Computer Speech & Language, 2014 – Elsevier … 2. The basic components of the Map Task dialogue system (Iteration 1) used for data collection. … For all three classifiers we used the implementations available in the WEKA toolkit (Hall et al., 2009). All results presented here are based on 10-fold cross-validation. 4.1. … Cited by 5 Related articles All 4 versions

Dialogue Act Modeling for Non-Visual Web Access V Ashok, Y Borodin, S Stoyanchev… – 15th Annual Meeting of …, 2014 – aclweb.org … 2009. The weka data mining software: an update. ACM SIGKDD explorations newsletter, 11 (1): 10– 18. Dan Klein and Christopher D Manning. 2003. … 2010. Re- cent approaches to dialog management for spoken dialog systems. JCSE, 4 (1): 1–22. George A Miller. 1995. … Cited by 3 Related articles All 8 versions

Formative feedback in an interactive spoken call system N Tsourakis, E Rayner, C Baur – 2014 – archive-ouverte.unige.ch … [15] Fuchs, M., Tsourakis, N. and Rayner, M., “A scalable architecture for web deployment of spoken dialogue systems”. … [22] Hall, M., Frank, E., Holmes, EG, Pfahringer, B., Reutemann, P. and Witten, I., “The WEKA Data Mining Software: An Update”. … Cited by 2 Related articles All 3 versions

Natural language generation as incremental planning under uncertainty: Adaptive information presentation for statistical dialogue systems V Rieser, O Lemon, S Keizer – Audio, Speech, and Language …, 2014 – ieeexplore.ieee.org … The majority of users were from a range of backgrounds in a higher education institute, in the age range 20-30, native speakers of English, and none had any prior experience of spoken dialogue systems. … 7The WEKA implementation of RIPPER [52]. … Cited by 2 Related articles All 7 versions

Korean anaphora recognition system to develop healthcare dialogue-type agent J Yang, Y Lee – Healthcare informatics research, 2014 – synapse.koreamed.org … NLP: Natural Language Processing, WEKA: Waikato Environment for Knowledge Analysis. … systems; it can be used either for deep semantic analysis of medical free-text to extract information and knowledge in an automatic manner or to design a dialogue system which can … Cited by 1 Related articles All 9 versions

Using hand gestures to control mobile spoken dialogue systems N Tsourakis – Universal Access in the Information Society, 2014 – Springer … In essence, these gestures constitute the minimum set that covers the basic functionalities of any spoken dialogue system. … The results of the different classification methods using the Weka Toolkit [ 11 ] are shown in Table 2, where it can be seen that most of the methods offer … Cited by 1 Related articles All 5 versions

Evaluation of a Fully Automatic Cooperative Persuasive Dialogue System T Hiraoka, G Neubig, S Sakti, T Toda, S Nakamura – uni-ulm.de … Policy Example database NLG NLU Text Text Dialogue system Fsys, Gsys uuser usys HGuser Fig. 1 Structure of our dialogue system. Rectangles represent information, and cylinders represent a system module. … We utilize Weka [13] for constructing the bagging classifier. … Related articles All 4 versions

Detecting Inappropriate Clarification Requests in Spoken Dialogue Systems A Liu, R Sloan, MV Then… – … of the 15th …, 2014 – academiccommons.columbia.edu … Our data consists of spoken answers to clarifica- tion requests collected at Columbia University us- ing a simulated dialogue system in order to … We used the Weka machine learning library (Wit- ten and Eibe, 2005) to train classifiers to predict whether a clarification request was … Cited by 1 All 10 versions

HALEF: an open-source standard-compliant telephony-based modular spoken dialog system–A review and an outlook D Suendermann-Oeft, V Ramanarayanan… – halef.org … IH: Weka: A machine learning workbench. In: Intelligent Information Systems, 1994. Proceedings of the 1994 Second Australian and New Zealand Conference on, pp. 357–361. IEEE (1994) 11. Jurc?cek, F., Dušek, O., Plátek, O., Zilka, L.: Alex: A statistical dialogue systems … Cited by 2 Related articles All 11 versions

An Analysis Towards Dialogue-based Deception Detection Y Tsunomori, G Neubig, S Sakti, T Toda, S Nakamura – uni-ulm.de … However this resource is not publicly available, and because we assume a one-on-one dialogue system, a corpus recorded with three … To solve this classification, we use Bagging of decision trees [1] as imple- mented in the Weka toolkit, which gave the best performance of the … Cited by 1 Related articles All 3 versions

Problematic Situation Analysis and Automatic Recognition for Chi-nese Online Conversational System Y Xiang, Y Zhang, X Zhou, X Wang, Y Qin – CLP 2014, 2014 – aclweb.org … Estimation Method of User Sat- isfaction Using N-gram-based Dialogue Histo- ry Model for Spoken Dialogue System. LREC. Mark Hall, Eibe Frank, Geoffrey Holmes, Bern- hard Pfahringer, Peter Reutemann, Ian H. Wit- ten. 2009. The WEKA Data Mining Software: An Update … Cited by 2 Related articles All 4 versions

Relationship between Student Writing Complexity and Physics Learning in a Text-Based ITS R Freedman, D Krieghbaum – Intelligent Tutoring Systems, 2014 – Springer … 1 http://nlp.stanford.edu/software/lex-parser.shtml 2 http://www.cs.waikato.ac.nz/ml/weka/ Page 2. … 1. Quinlan, J.: C4.5: Programs for Machine Learning. Morgan Kaufman, San Mateo (1992) 2. Litman, D., Silliman, S.: ITSPOKE: An Intelligent Tutoring Spoken Dialogue System. … Related articles

Entrainment in pedestrian direction giving: How many kinds of entrainment Z Hu, G Halberg, C Jimenez, M Walker – Proc. IWSDS, 2014 – uni-ulm.de … We use Linear Regression in Weka 3.6.1 with 10-fold cross validation. Fig. … RandomHumanUtterance has the second highest positive weight. Proceedings of 5th International Workshop on Spoken Dialog Systems Napa, January 17-20, 2014 97 Page 9. … Cited by 4 Related articles

Modelling User Experience in Human-Robot Interactions K Jokinen, G Wilcock – Multimodal Analyses enabling Artificial Agents in …, 2014 – Springer … In spoken dialogue systems [12] this has been an important design principle discussed under the concepts of grounding and feedback. … Following our previous studies [13], we used Weka [21] to run classification algo- rithms to estimate how well the annotation features of a … Related articles All 3 versions

Detecting Incorrectly-Segmented Utterances for Posteriori Restoration of Turn-Taking and ASR Results N Hotta, K Komatani, S Sato… – … Annual Conference of …, 2014 – mazsola.iit.uni-miskolc.hu … viewpoint, spoken dialogue systems should also not start speak- ing while the user is speaking [1]. However, sometimes a spoken dialogue system will mis … build a decision tree by removing a feature one by one and then 1http://www.cs.waikato.ac.nz/ml/weka/ 2http://opensmile … Cited by 2 Related articles All 5 versions

Question Classification in an Epistemic Game H Li, B Samei, AM Olney, AC Graesser, DW Shaffer – 2014 – edgaps.org … The prior research on automated question classification focused on ei- ther the feature selections in dialog systems [10,11] or question taxonomy in tutoring … The present study employed a J48 decision tree to train and test the model of ques- tion classification with WEKA [17]. … Related articles

Nonstrict hierarchical reinforcement learning for interactive systems and robots H Cuayáhuitl, I Kruijff-Korbayová… – ACM Transactions on …, 2014 – dl.acm.org … Thomaz and Breazeal 2006]. While reinforcement learning dialogue systems are thus very promising, they still need to overcome several limitations to reach practical and widespread application in the real world. One of these … Cited by 3 Related articles

Challenges for robust prosody-based affect recognition H Pon-Barry, AR Nelakurthi – Proceedings of Speech Prosody, 2014 – ponbarry.com … affect [11]. In applications such as spoken dialogue systems for tutoring students, we are most in- terested in knowing a student’s internal level of certainty. Prior … all speakers). PCA is performed using the WEKA toolkit [21]. The … Cited by 3 Related articles

Cluster-based Prediction of User Ratings for Stylistic Surface Realisation N Dethlefs, H Cuayáhuitl, H Hastie, V Rieser… – EACL …, 2014 – anthology.aclweb.org … Fu- ture work involves integrating the surface realiser into the PARLANCE1 (Hastie et al., 2013) spo- ken dialogue system with a method for triggering the different styles. … We used the R statistics toolkit7 for the MMR and the Weka toolkit8 for the remaining models. … Cited by 5 Related articles All 11 versions

Framework for Data Processing A Osherenko – Social Interaction, Globalization and Computer-Aided …, 2014 – Springer … files using a desired mathematical algorithm such as SVM or NaïveBayes (Ap- pendix B). Since our approach is based on HMMs, an HMM classifier is developed that is compatible with the WEKA toolkit and … 6.3.2), the button Dialog system starts a sequential dialog system (Sect … Related articles

Non-Strict Hierarchical Reinforcement Learning for Interactive Systems and Robots HC AHUITL, N DETHLEFS – macs.hw.ac.uk … Thomaz and Breazeal 2006]. While reinforcement learning dialogue systems are thus very promising, they still need to over- come several limitations to reach practical and wide-spread application in the real world. One of these … Related articles All 3 versions

Validating Attention Classifiers for Multi-Party Human-Robot Interaction ME Foster – workshops.acin.tuwien.ac.at … 7. REFERENCES [1] Weka primer. http://weka.wikispaces.com/Primer. [2] D. Aha and D. Kibler. … [5] D. Bohus and E. Horvitz. Learning to predict engagement with a spoken dialog system in open-world settings. In Proceedings of SIGDial, 2009. … Cited by 1 Related articles All 2 versions

Predicting semantic changes in abstraction in tutor responses to students M Lipschultz, D Litman, S Katz… – … Journal of Learning …, 2014 – inderscienceonline.com … Our project started with a fully-automatic interactive post-problem reflective dialogue system for physics and modified the reflective dialogue system so that it simulates dialogue decision rules that we predict should improve student learning, relative to a control dialogue system … Cited by 1 Related articles All 6 versions

A methodology for using crowdsourced data to measure uncertainty in natural speech L Martin, M Stone, F Metze… – … Workshop (SLT), 2014 …, 2014 – ieeexplore.ieee.org … we implemented a naive Bayes tree (a tree with different Naive Bayes classi- fiers at the leaves) created by Weka [10], training and … Regardless, dif- ferent prosodic cues should be experimented with, such as the 76 various spoken features extracted for dialog systems in work by … Related articles All 6 versions

Investigation of Speaker Group-Dependent Modelling for Recognition of Affective States from Speech I Siegert, D Philippou-Hübner, K Hartmann, R Böck… – Cognitive …, 2014 – Springer … p. 308–315. Gnjatovi? M, Rösner D. On the role of the NIMITEK corpus in developing an emotion adaptive spoken dialogue system. In: Proceedings of the 7th LREC. Marrakech, Morocco; 2008. … The weka data mining software: an update. SIGKDD Explor Newsl. … Cited by 3 Related articles All 2 versions

Context?Sensitive Natural Language Generation: From Knowledge?Driven to Data?Driven Techniques N Dethlefs – Language and Linguistics Compass, 2014 – Wiley Online Library … Training was done using the Weka toolkit (Witten and Frank 2005). … Janarthanam and Lemon (2010) present an interesting application of RL to audience design in the context of a spoken dialogue system, which helps users set up their home broadband connection. … Cited by 3 Related articles All 4 versions

Towards A General Method for Building Predictive Models of Learner Success using Educational Time Series Data. CA Brooks, C Thompson, SD Teasley – LAK Workshops, 2014 – ceur-ws.org … chat or discussion forums, some have also applied intelligent systems in the form of peer matching [4] or tutors based on dialogue systems [7]. In … To address these questions, we formed predictive mod- els with J48 decision trees using the weka toolkit [8]. For each model, we … Cited by 1 Related articles

Turn-taking, feedback and joint attention in situated human–robot interaction G Skantze, A Hjalmarsson, C Oertel – Speech Communication, 2014 – Elsevier … Contrary to this sophisticated combination of cues for managing turn-taking, dialogue systems have traditionally only used a fixed silence threshold, after which the system starts to process the utterance and generate a response. … 3.1. A Map Task dialogue system. … Cited by 8 Related articles All 4 versions

T-PICE: Twitter Personality based Influential Communities Extraction System E Kafeza, A Kanavos, C Makris… – Big Data (BigData …, 2014 – ieeexplore.ieee.org … Classification algorithms from the Weka toolkit are used to map these user profiles to personality traits. … These studies have introduced methods of recognition of the blogger’s personality [19] or speech based dialogue system understanding a user’s personality [1]; datasets from … Cited by 5 Related articles All 2 versions

Prototypes of Social Simulation A Osherenko – Social Interaction, Globalization and Computer-Aided …, 2014 – Springer … For this purpose, SocioFramework extracts 526 stopwords from the WEKA toolkit (Witten and Frank 2005) in deictic datasets. … affect sensing in an SS system can rely on an approach that uses the SPIN parser (Engel 2006), a semantic parser for spoken dialog systems, to detect … Related articles

Intelligent Systems’ Holistic Evolving Analysis of Real-Life Universal Speaker Characteristics B Schuller, Y Zhang, F Eyben… – Proceedings of the 5th …, 2014 – mediatum.ub.tum.de … spite them being crucial for real-life applications such as retrieval, dialogue systems and computer-mediated human- to-human conversation. … 2012 Speaker Trait Challenge and perform multi-task learning with the MEKA toolkit, which is an extension to the WEKA machine learn … Cited by 2 Related articles All 2 versions

Adaptive Tutoring for Self-Regulated Learning: A Tutorial on Tutoring Systems RA Sottilare, AM Sinatra – researchgate.net Page 1. Adaptive Tutoring for Self-Regulated Learning: A Tutorial on Tutoring Systems by Robert A Sottilare and Anne M Sinatra ARL-SR-0305 December 2014 Approved for public release; distribution is unlimited. Page 2. NOTICES Disclaimers … Related articles

Linguistic and multilingual issues in virtual worlds and serious games: a general review S Cruz-Lara, A Denis, N Bellalem – The Journal of Virtual Worlds …, 2014 – hal.inria.fr … partially sighted people, and enrich their experience of the content; emotion recognition (eg, for spotting angry customers in speech dialog systems); support for … Thanks to the WEKA library (data mining software in Java, http://www.cs.waikato.ac.nz/ml/weka/), after importing our … Related articles All 7 versions

Improving Speech Recognition through Automatic Selection of Age Group–Specific Acoustic Models A Hämäläinen, H Meinedo, M Tjalve… – … Processing of the …, 2014 – Springer … In spoken dialogue systems, an age group classifier might be useful for selecting dialogue strategies or different ways of interacting with the user. … Hamilton, New Zealand (1998) [29] Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.: The WEKA Data Mining … Cited by 1 Related articles All 6 versions

Generation of effective referring expressions in situated context K Garoufi, A Koller – Language, Cognition and Neuroscience, 2014 – Taylor & Francis … Janarthanam, S., & Lemon, O. (2010). Learning to adapt to unknown users: Referring expression generation in spoken dialogue systems. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics. Uppsala, Sweden. View all references). … Cited by 7 Related articles All 2 versions

Automated Indexing of Internet Stories for Health Behavior Change: Weight Loss Attitude Pilot Study R Manuvinakurike, WF Velicer… – Journal of medical …, 2014 – ncbi.nlm.nih.gov … Indexing Algorithm Training and Accuracy Results. The stage of change classification algorithm training was performed using Adaptive Boosting (AdaBoost) [39] with weak learners using Weka [40]. … 14. Bickmore T, Giorgino T. Health dialog systems for patients and consumers. … Related articles All 8 versions

Detecting Address Estimation Errors from Users’ Reactions in Multi-user Agent Conversation R Hotta, HH Huang, S Otogi, K Kawagoe – Human-Computer Interaction. …, 2014 – Springer … Dowding, J., Alena, R., Clancey, WJ, Sierhuis, M., Graham, J.: Are you talking to me? dialogue systems supporting mixed teams of humans and robots. … Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, IH: The weka data mining software: An update. … Related articles

Hierarchical stress generation with Fujisaki model in expressive speech synthesis Y Li, J Tao, K Hirose, W Lai, X Xu – Speech Prosody, 2014 – speakit.cn … [12] S. Kiriyama, K. Hirose, and N. Minematsu, “Prosodic focus control in reply speech generation for a spoken dialogue system of information retrieval,” in … [16] M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and IH Witten, “The WEKA Data Mining Software: An … Cited by 1 Related articles

Machine Learning for Social Multiparty Human–Robot Interaction S Keizer, M Ellen Foster, Z Wang… – ACM Transactions on …, 2014 – dl.acm.org … Classifiers. Using the Weka data mining toolkit [Hall et al. 2009], we experimented with a number of different supervised learning classifiers to see which performed the best on this particular labeling task. Since we had no prior … Cited by 3 Related articles All 2 versions

Comparing multi-label classification with reinforcement learning for summarisation of timeseries data D Gkatzia, H Hastie, O Lemon – 52nd Annual Meeting of the …, 2014 – macs.hw.ac.uk … et al., 2010). 4.2.1 The Production Phase of RAkEL The algorithm was implemented using the MU- LAN Open Source Java library (Tsoumakas et al., 2011), which is based on WEKA (Witten and Frank, 2005). The algorithm works … Cited by 5 Related articles All 10 versions

A framework for the assessment of synthetic personalities according to user perception Z Callejas, D Griol, R López-Cózar – International Journal of Human- …, 2014 – Elsevier … conducts. The comparison was carried out using likeability and trustworthiness measures obtained from questionnaires, as well as typical dialogue system measures such as ease of understanding and helpfulness. Additionally … Cited by 4 Related articles All 5 versions

Triggering effective social support for online groups R Kumar, CP Rosé – … Transactions on Interactive Intelligent Systems (TiiS …, 2014 – dl.acm.org … In line with recent developments in data-driven approaches for building dialog systems, we present a novel technique for learning behavior- specific triggering policies, deploying it as part of our efforts to improve a socially capable conversational tutor agent that supports … Cited by 3 Related articles

Automatic scoring for answers to Arabic test questions WH Gomaa, AA Fahmy – Computer Speech & Language, 2014 – Elsevier … The UKP-BIU (Torsten Zesch et al., 2013) system was based on training a supervised model (Naive Bayes) using Weka (Hall et al., 2009), with feature extraction based on clearTK (Ogren et al., 2008 … It has been used in the tutorial dialog system Why2-Atlas (VanLehn et al., 2002 … Cited by 4 Related articles All 4 versions

Aspectual Properties of Conversational Activities RJ Passonneau, B Guan, CH Yeung, Y Du… – 15th Annual Meeting of …, 2014 – aclweb.org … and Cost Annotation (TSCA), was aimed at identifying individual dialog tasks analogous to those carried out by spoken dialog systems, to fa … Four machine learning methods were tested us- ing the Weka toolkit (Hall et al., 2009): Naive Bayes, J48 Decision Trees, Logistic … Related articles All 8 versions

Interpreting Natural Language Instructions Using Language, Vision, and Behavior L Benotti, T Lau, M Villalba – ACM Transactions on Interactive Intelligent …, 2014 – dl.acm.org … We implemented the LIBSVM wrapper described in Chang and Lin [2011] with a radial kernel and default parameters, and the DTs were implemented using the classifier J48, as used in the machine learning WEKA package [Hall et al. 2009]. … Cited by 1 Related articles

A Survey on Mobile Affective Computing S Zhang, P Hui – arXiv preprint arXiv:1410.1648, 2014 – arxiv.org … process. For these tasks, they used a popular machine learning software toolkit named Weka [?]. … emotion. All of these features are formalized as an attribute-relation file format (ARFF) for Weka. They analyzed collected training data using W All 2 versions

Affect detection from non-stationary physiological data using ensemble classifiers O AlZoubi, D Fossati, S D’Mello, RA Calvo – Evolving Systems, 2014 – Springer … A down-sampling procedure, WEKA’s SpreadSubsample which produces a random sub- sample of a dataset, was applied to obtain a balanced dis- tribution of classes. … 2009). The WEKA machine learning software (Witten and Frank 2005) and PRTools 4.0 (Heijden et al. … Cited by 1 Related articles All 2 versions

Towards Modeling Collaborative Task Oriented Multimodal Human-human Dialogues L Chen – 2014 – indigo.uic.edu … xi Page 13. CHAPTER 1 INTRODUCTION A dialogue system is a computer system intended to converse with a human. The input … of communication. The most widely researched and developed dialogue systems are spoken dialogue sys- … All 3 versions

ZureTTS: Online Platform for Obtaining Personalized Synthetic Voices D Erro, I Hernáez, E Navas, A Alonso, H Arzelus, I Jauk… – aholab.ehu.es Page 1. ENTERFACE’14 – ZURETTS 1 ZureTTS: Online Platform for Obtaining Personalized Synthetic Voices Daniel Erro?, Inma Hernáez?, Eva Navas?, Agust?n Alonso, Haritz Arzelus, Igor Jauk, Nguyen Quy Hy, Carmen Magari … Cited by 2 Related articles All 3 versions

[BOOK] Text Mining of Web-based Medical Content A Neustein – 2014 – books.google.com … visu- ally impaired. The author shows how this health dialogue system provides health information about lassa fever, malaria fever, typhoid fever and yellow fever to those who cannot access this information on line. The author … Related articles All 4 versions

Robust Object Classification in Underwater Sidescan Sonar Images by Using Reliability-Aware Fusion of Shadow Features N Kumar, U Mitra, SS Narayanan – 2014 – ieeexplore.ieee.org … in automatic speech recognition tasks [12], [13], where these models are used to identify out of vo- cabulary (OOV) words in dialog systems [14] or … The fusion methods are im- plemented via the WEKA toolkit [34]. In Section VII, we also compare against a score fusion scheme. … Cited by 2 Related articles All 2 versions

[BOOK] Robust Methods for Content Analysis of Auditory Scenes JT Geiger – 2014 – mediatum.ub.tum.de … Audio recognition methods are also used in robotics. For example, service robots with a multimodal dialogue system can improve their understanding of the environ- ment with techniques for speech and audio recognition [10]. … The implementation of the Weka toolkit [94] is used. … Related articles All 3 versions

Enabling Non-Speech Experts to Develop Usable Speech-User Interfaces A Kumar – 2014 – reports-archive.adm.cs.cmu.edu … developed world. For users in developing regions, where illiteracy often impedes usage of graphical interfaces, spoken dialog systems are being explored to provide access to relevant information, such as weather information to farmers [Plauchè et al., 2006], medical advise to … Related articles All 3 versions

An Artificial Intelligence Framework for Investigative Reasoning R Ramezani – 2014 – wwwhomes.doc.ic.ac.uk … 2.7.2 Apriori Algorithm . . . . . 35 2.7.3 Weka . . . . . … 4.5.2 Translation to HR . . . . . 92 4.5.3 Translation to Weka – Data Flattening for Weka . . . . . 93 4.6 Conclusions . . . . . … Related articles All 4 versions

Maximum likelihood inverse reinforcement learning MC Vroman – 2014 – rucore.libraries.rutgers.edu Page 1. MAXIMUM LIKELIHOOD INVERSE REINFORCEMENT LEARNING by MONICA C. VROMAN A dissertation submitted to the Graduate School—New Brunswick Rutgers, The State University of New Jersey In partial fulfillment of the requirements For the degree of … Related articles All 4 versions

Semi-automatic Domain Modeling from Multilingual Corpora S Pollak – 2014 – kt.ijs.si Page 1. Univerza v Ljubljani/University of Ljubjana Filozofska fakulteta/Faculty of Arts Oddelek za prevajalstvo/Department of Translation Senja Pollak Polavtomatsko modeliranje podro?nega znanja iz ve?jezi?nih korpusov Semi … Cited by 1 Related articles

Detecting Sarcasm on Twitter: A Behavior Modeling Approach A Rajadesingan – 2014 – repository.asu.edu Page 1. Detecting Sarcasm on Twitter: A Behavior Modeling Approach by Ashwin Rajadesingan A Thesis Presented in Partial Fulfillment of the Requirement for the Degree Master of Science Approved September 2014 by the Graduate Supervisory Committee: … Related articles