Named-Entity Recognition & Dialog Systems 2014


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Named-Entity Recognition & Dialog Systems 2015


A survey of arabic named entity recognition and classification K Shaalan – Computational Linguistics, 2014 – MIT Press … A Survey of Arabic Named Entity Recognition and Classification. … Named Entity Recognition (NER) is an Information Extraction task that has become an integral part of many other Natural Language Processing (NLP) tasks, such as Machine Translation and Information Retrieval. … Cited by 29 Related articles All 15 versions

Hypotheses ranking for robust domain classification and tracking in dialogue systems. JP Robichaud, PA Crook, P Xu, OZ Khan… – …, 2014 – mazsola.iit.uni-miskolc.hu … [5] T.-VT Nguyen, A. Moschitti, and G. Riccardi, “Kernel-based re- ranking for named-entity recognition,” in Proceedings of the … DR Traum, and SS Narayanan, “A reranking approach for recognition and classification of speech input in conversational dialogue systems.” in IEEE … Cited by 6 Related articles All 11 versions

SiAM-dp: A Platform for the Model-Based Development of Context-Aware Multimodal Dialogue Applications. R Nesselrath, M Feld – Intelligent Environments, 2014 – researchgate.net … 245–246. [19] I. Gurevych, R. Porzel, E. Slinko, N. Pfleger, J. Alexandersson, and S. Merten, “Less is more: Using a single knowledge representation in dialogue systems,” in Proceedings of … [23] D. Nadeau and S. Sekine, “A survey of named entity recognition and classification … Cited by 6 Related articles All 4 versions

[BOOK] Natural language processing of semitic languages I Zitouni – 2014 – Springer … 238 7.6 Labeled Named Entity Recognition Corpora….. … Prior to IBM, Imed was a researcher at Bell Laboratories, Lucent Technologies, for almost half dozen years working on language modeling, speech recognition, spoken dialog systems, and speech understanding. … Cited by 10 Related articles All 6 versions

An end-to-end dialog system for tv program discovery D Ramachandran, PZ Yeh, W Jarrold… – … (SLT), 2014 IEEE, 2014 – ieeexplore.ieee.org … In this paper, we presented an end-to-end dialog system for TV program discovery whose salient features include: 1) a trainable … J. Sterling, E. Agichtein, and R. Grish- man, “Exploiting diverse knowledge sources via max- imum entropy in named entity recognition,” in Sixth … Cited by 3 Related articles

R-cube: a dialogue agent for restaurant recommendation and reservation S Kim, RE Banchs – Signal and Information Processing …, 2014 – ieeexplore.ieee.org … For the implementation of the three sub-systems, a multi-strategy architecture, which is depicted in Figure 1, has been adopted. Figure 1. Multi-strategy Dialogue System Architecture … ASR & Preprocessing Named Entity Recognition Dialog Act Identification Dialog Management … Cited by 3 Related articles All 2 versions

Advances in Wikipedia-based Interaction with Robots G Wilcock, K Jokinen – Proceedings of the 2014 Workshop on …, 2014 – dl.acm.org … systems in which the robot and the human can take turns in talking more and lis- tening more in changing proportions. This capability is now becoming feasible due to advances both in open-vocabulary speech recognition and in Wikipedia-based named entity recognition. … Cited by 2 Related articles All 4 versions

Sentiment analysis of Arabic slang comments on facebook TH Soliman, MA Elmasry, A Hedar… – International Journal of …, 2014 – researchgate.net … S., Elarnaoty, M., Magdy, M. and Fahmy, A. (2010) Integrated machine learning techniques for Arabic named entity recognition, IJCSI International … Hijjawi, M. and Bander, Z. (2011) An Arabic Stemming approach using machine learning with Arabic dialogue system, ICGST AIML … Cited by 3 Related articles All 2 versions

A Chinese Question Answering System for Specific Domain T Li, Y Hao, X Zhu, X Zhang – International Conference on Web-Age …, 2014 – Springer … which includes: 1) natural language understanding, 2) knowledge base construction, management and query, 3) dialog system techniques. … Natural Lan- guage Understanding unit (NLU) transforms questions into semantic frames via named entity recognition and patterns. … Cited by 1 Related articles

A novel feature selection strategy for enhanced biomedical event extraction using the turku system J Xia, AC Fang, X Zhang – BioMed research international, 2014 – hindawi.com … As a result of this information explosion, text mining and linguistic methods have been used to perform automatic named entity recognition (NER) including biomedical NER [4], the extraction of clinical narratives [5] and clinical trials [6], analysis of the similarity in gene ontology [7 … Cited by 3 Related articles All 10 versions

Two-stage stochastic natural language generation for email synthesis by modeling sender style and topic structure YN Chen, AI Rudnicky – Proceedings of INLG, 2014 – aclweb.org … A lot of NLG systems are applied in dialogue systems, some of which focus on topic model- ing (Sauper and Barzilay, 2009; Barzilay and Lap- ata, 2008; Barzilay and Lee, 2004 … 1 General Class We use existing named entity recognition (NER) tools for identifying general classes … Cited by 2 Related articles All 14 versions

Inter-annotator agreement on spontaneous Czech language T Valenta, L Šmídl, J Švec, D Soutner – International Conference on Text, …, 2014 – Springer … The inter-annotator agreement of classification tasks such as assigning labels from few classes (eg parts-of-speech tagging, named entity recognition etc.) is commonly evaluated. … To record the corpus, a simple dialogue system was developed. … Cited by 2 Related articles All 8 versions

Topics for the future: Genre differentiation, annotation, and linguistic content integration in interaction analysis F Bonin, E Gilmartin, C Vogel, N Campbell – Proceedings of the 2014 …, 2014 – dl.acm.org … Indeed, dialogue system technology is based on task-based dialogue [1] for reasons of tractability. … novel technolo- gies should take advantage of all the available information to tackle tasks which might be tractable with clean inputs (such as named entity recognition or semantic … Cited by 3 Related articles

Toward an ontology-based chatbot endowed with natural language processing and generation A Hallili – 26th European Summer School in Logic, Language & …, 2014 – hal.inria.fr … focus on modeling and implementing an efficient and robust QA system that will be the corner stone for our future Dialog System. … Named Entity Recognition : To identify the NE, we aim at using natural language processing techniques (eg Named Entity detection and linking) to … Cited by 1 Related articles All 12 versions

Question answering system S Nalawade, S Kumar, D Tiwari – … Journal of Science and Research (IJSR), 2014 – ijsr.net … Since 1960s, till the field was in its infancy, a variety of natural language database front-ends, dialog systems, and language understanding … Named Entity Recognition :Named Entity (NE) Recognition is a specialized form of the IE task dedicated to identifying phrases in text that … Cited by 1 Related articles All 2 versions

An introduction to question answering over linked data C Unger, A Freitas, P Cimiano – Reasoning Web International Summer …, 2014 – Springer … It also involves steps like Named Entity Recognition. In addition, a question can be analysed with respect to the categories mentioned above, in particular detecting the question type, the focus and the expected answer type. … Cited by 10 Related articles All 5 versions

Automatic creation of semantic data about football transfer in sport news QM Nguyen, TD Cao, TT Nguyen – Proceedings of the 16th International …, 2014 – dl.acm.org … fields [16]. Smartweb System [4] is a multi-dialog system arising answers from the semantic web services. The above … syntax analyzer. A named entity recognition (NER) stage is performed using the C & C NER tagger. After the … Cited by 1 Related articles

Human annotation of ASR error regions: Is “gravity” a sharable concept for human annotators? D Luzzati, C Grouin, I Vasilescu, M Adda-Decker… – …, 2014 – pdfs.semanticscholar.org … When judging errors on a common seriousness scale, do judges follow different strategies (eg, are errors harmful wrt global understanding, language syntax, dialog systems, named entity recognition, etc.) de- pending on their personal competence and interests or is there a … Cited by 4 Related articles All 4 versions

Word embeddings: A semi-supervised learning method for slot-filling in spoken dialog systems X Yang, Z Chen, J Liu – Chinese Spoken Language Processing …, 2014 – ieeexplore.ieee.org … We are also able to do significantly better slot filling on a noisy text, which is a promising setting for spoken dialog systems in real life. … [17] J. Turian, L. Ratinov, Y. Bengio, and D. Roth, “A prelim- inary evaluation of word representations for named-entity recognition,” in NIPS … Related articles All 2 versions

Domain Specific Named Entity Recognition (DSNER) from Web Documents P Kumar, RK Goel, PS Sharma – International Journal of …, 2014 – search.proquest.com … a document that refer to proper names of any kind (person, organization, location etc.) can be described as Named Entity Recognition (NER). … representations of sentences like in the case of Information Extraction systems [2][3] and Human-Machine Dialogue systems or merely … Related articles All 5 versions

Learning an Optimal Sequence of Questions for the Disambiguation of Queries over Structured Data A Rettinger, A Hagemann… – Workshops at the …, 2014 – pdfs.semanticscholar.org … disambigua- tion, setting itself off against previous work on interactive and adaptive dialogue systems for disambiguation in … Keywords: Question Answering, Relational Reinforcement Learning, Information Retrieval, Linked Data, Named-Entity Recognition, Disambiguation … Related articles All 2 versions

Conditional Random Field In Segmentation And Noun Phrase Inclination Tasks For Russian AA Romanenko, P II – dialog-21.ru … It may be useful in data mining applications. Temporal expressions extraction is important for natural language under- standing modules of spoken dialog systems. … The task of temporal expressions extraction is a kind of named entity recognition task common in NLP. … Related articles

Language Resources and Technology in Latvia (2010-2014) I Skadi?a, I Auzi?a, G B?rzdi?š… – … : Proceedings of the …, 2014 – books.google.com … 4.8. Multimedia Novel research has been started to apply language technologies to dialog systems for smartphones. Two virtual agents are currently under development in Latvia. … Pinnis, M. Latvian and Lithuanian Named Entity Recognition with TildeNER. … Related articles All 4 versions

Exploiting out-of-vocabulary words for out-of-domain detection in dialog systems S Ryu, D Lee, GG Lee, K Kim… – … Conference on Big Data …, 2014 – ieeexplore.ieee.org … for humans to design; ie obtain reliable training data from original training data by consulting HDM is difficult in those dialog systems. … of NLU simultaneously models all or a subset of NLU processes: domain detection, dialog act classification, and named entity recognition [2,4,11 … Related articles All 3 versions

SemEval-2014 Task 2: Grammar Induction for Spoken Dialogue Systems I Klasinas, E Iosif, K Louka, A Potamianos – SemEval 2014, 2014 – Citeseer … Automatic or machine-aided gram- mar creation for spoken dialogue systems can be broadly divided in two categories (Wang and Acero … In such cases, gazetteer lookup and named entity recognition can be employed (if the respective resources and tools are available), as well … Related articles All 13 versions

A Framework for Health Behavior Change using Companionable Robots B Sarma, A Das, RD Nielsen – INLG 2014, 2014 – Citeseer … and therapeutic. 2 Framework The proposed dialogue system framework con- sists of three broad stages. The … ated behaviors. These conditions will be identi- fied primarily using named-entity recognition and keyword spotting. If … Cited by 1 Related articles All 12 versions

Syn! Bad: A Synonym-Based Regular Expression Extension For Knowledge Extraction Task. O ?ERBAN – Studia Universitatis Babes-Bolyai, Informatica, 2014 – search.ebscohost.com … Most of the sentence tokenization algorithms are based on regular expressions [8, 2]. Moreover, more complex tasks, such as Part- of-Speech Tagging (POS) [13] or Named Entity Recognition (NER) [10] use them … Knowledge Extraction, Dialogue Systems, Regular Expressions. … Related articles

[BOOK] Human Language Technology Challenges for Computer Science and Linguistics: 5th Language and Technology Conference, LTC 2011, Pozna?, Poland, … Z Vetulani, J Mariani – 2014 – books.google.com … a further contribution to the intonational modelling of backchannels in Italian, useful for improving naturalness in voice-based dialogue systems for this … The seventh paper presents results on applying text mining techniques to named entity recognition (Nouvel, Antoine, Friburger …

Two-Stage Stochastic Email Synthesizer YN Chen, AI Rudnicky – INLG 2014, 2014 – aclweb.org … We also annotate content slots, including general classes automatically created by named entity recognition (NER)(Finkel et al., 2005) and hand-crafted topic classes, to model text content for surface realization … Stochastic natural language generation for spoken dialog systems. … Related articles All 14 versions

Optimization Tasks in the Conversion of Natural Language Texts into Function Calls P Barabás, L Kovács – Applied Information Science, Engineering and …, 2014 – Springer … tasks. Our goal is to define and implement a natural language framework using a frame-based dialog system that can be applied to robot control. … The analysis consists of two phases: spell checking and named-entity recognition. There … Related articles All 3 versions

Evaluation of Invalid Input Discrimination Using Bag-of-Words for Speech-Oriented Guidance System H Majima, R Torres, H Kawanami, S Hara… – Natural Interaction with …, 2014 – Springer … learning technique for classification and prediction, which has been successfully applied to natural language processing, named entity recognition, etc … Lee, A., Nakamura, K., Nishimura, R., Saruwatari, H., Shikano, K.: Noise robust real world spoken dialogue system using GMM … Related articles All 5 versions

Question answering system: A heuristic approach V Bhoir, MA Potey – Applications of Digital Information and Web …, 2014 – ieeexplore.ieee.org … RELATED WORK Since 1960s, a variety of natural language database frontends, dialog systems and language understanding systems were … There are different IE techniques [15] like Template Matching, Named Entity Recognition (NER) and Automated Content Extraction (ACE … Related articles All 2 versions

Understanding questions and finding answers: semantic relation annotation to compute the Expected Answer Type V Petukhova – Proceedings 10th Joint ISO-ACL SIGSEM Workshop on …, 2014 – lrec-conf.org … The system has all components that any traditional dialogue system has: Automatic Speech Recog- nition (ASR) and Speech Generation (eg TTS) modules, and the Dialogue Engine. … 2009. Design challenges and mis- conceptions in named entity recognition. … Related articles All 4 versions

QAS SD Joshi – International Journal of Application or Innovation in …, 2014 – academia.edu … Since 1960s, a variety of natural language database frontends, dialog systems and language understanding systems were created. … There are different IE techniques [15] like Template Matching, Named Entity Recognition (NER) and Automated Content Extraction (ACE).QAS … Related articles All 2 versions

Cluster based Chinese abbreviation modeling. Y Shi, YC Pan, MY Hwang – INTERSPEECH, 2014 – mazsola.iit.uni-miskolc.hu … In some practical applications (eg dialogue systems and voice search systems), document level context information is not available. … [3] J. Gao, M. Li, C.-N. Huang, and A. Wu, “Chinese word segmenta- tion and named entity recognition: A pragmatic approach.” Com- putational … Related articles All 5 versions

Computational Hispanic Linguistics MA Martí, M Taulé – The Routledge Handbook of Hispanic …, 2014 – books.google.com … These applications (machine translation, question answering, information extrac- tion, and dialog systems, among others) are based on an … QA systems complex language technologies are applied, such as PoS tagging, syntactic parsing, and Named Entity Recognition (NER) 23 … Related articles

Global Intelligent Content: Active Curation of Language Resources using Linked Data. D Lewis, R Brennan, L Finn, D Jones, A Meehan… – LREC, 2014 – lrec-conf.org … filtering of automated term extraction or human Wizard of Oz intervention in multimodal interactive dialogue systems, the semantic … include machine translation and text analytics engines that may assist translators with tasks such as named entity recognition and disambiguation. … Cited by 3 Related articles All 4 versions

Core technologies for the internet of services T Becker, C Burghart, K Nazemi, P Ndjiki-Nya… – Towards the Internet of …, 2014 – Springer … shell provides – for the first time – a developer with an integrated development environment (IDE) for the various, diverse tasks in a dialog system. … Thus, whereas named entity recognition identifies Kohl as a person’s name and China as a country (and not as a ceramic), relation … Cited by 3 Related articles All 3 versions

Joint Morphological Generation and Syntactic Linearization. L Song, Y Zhang, K Song, Q Liu – AAAI, 2014 – people.sutd.edu.sg … 2008; Sun 2011), joint named entity recognition and parsing (Finkel and Manning 2009), joint Chinese word segmentation, part-of-speech tagging and parsing (Zhang et al. 2013; Hatori et al. 2012) and joint morphological tag- ging and parsing (Bohnet et al. 2013). … Cited by 6 Related articles All 5 versions

Realistic Dialogue Engine for Video Games CM Rose – 2014 – ir.lib.uwo.ca … 59 6.4.3 Named Entity Recognition and Classification ….. 60 … after a while due to the highly deterministic nature of their responses. The types of dialogue systems used in video games could be classified into three main … Cited by 1 Related articles

Arabic-Malay Machine Translation Using Rule-Based Approach AJ Alsaket, MJ Ab Aziz – Journal of Computer Science, 2014 – search.proquest.com … Almeshrky, HA and MJA Aziz, 2012. Arabic malay machine translation for a dialogue system. J. Applied Sci., 12: 1371-1377. DOI: 10.3923/jas.2012.1371.1377. Attia, MA, 2007. … Benajiba, Y., 2009. Arabic named entity recognition. Ph.D. Thesis, University of Valencia, Spain. … Cited by 1 Related articles All 3 versions

No Evidence Left Behind: Understanding Semantics in Dialogs using Relational Evidence Based Learning A Celikyilmaz, D Hakkani-Tur, M Jeong – msr-waypoint.net … the baselines. 1 Introduction A typical spoken language understanding (SLU) en- gine of a conversational dialog system represents utterances of different domains (eg, news, travel, etc.) with semantic components. These compo … Related articles All 5 versions

Language Models and Interfaces 2015 I Titov – Citeseer … Dialog: Systems that communicate with people through language. Examples: dialog systems Question: how does language play a role in these systems? Page 6. … 3. How long will it take? Named entity recognition, co-reference (pronoun) resolution Example task Page 9. 4 … All 3 versions

A comparative evaluation methodology for nlg in interactive systems H Hastie, A Belz – 2014 – eprints.brighton.ac.uk … For example, the overall goal of a dialogue system eval- uation may be to assess ‘Dialogue Performance’. … Finally, the task in GREC-NER was a straightforward combined Named-Entity Recognition and coreference resolution task, restricted to people entities. … Cited by 3 Related articles All 9 versions

A Semi-Supervised Clustering Approach for Semantic Slot Labelling H Cuayáhuitl, N Dethlefs… – Machine Learning and …, 2014 – ieeexplore.ieee.org … For example, [14] applies semi- supervised learning to named-entity recognition and Chinese word segmentation. … methods and supervised classifiers using the method described above; an (5) perform an extrinsic evaluation with an end-to-end spoken dialogue system [34]. … Cited by 2 Related articles All 6 versions

Statistical Dialog Management for Health Interventions U Yasavur – 2014 – digitalcommons.fiu.edu … Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains … based on the brief intervention counseling style via spoken dialogue systems. … Related articles All 3 versions

A Survey of Intelligent Language Tutoring Systems M Al Emran, K Shaalan – Advances in Computing, …, 2014 – ieeexplore.ieee.org … 6. Beetle II System Beetle II system is a tutorial dialogue system that has been implemented to accept input from the learner without restrictions and to provide experimentation … A Survey of Arabic Named Entity Recognition and Classification, Computational Linguistics, MIT Press … Cited by 1 Related articles All 6 versions

A Survey on Large Scale Corpora and Emotion Corpora M Ptaszynski, R Rzepka, S Oyama, M Kurihara… – Information and Media …, 2014 – jlc.jst.go.jp … for training many AI applica- tions, from part-of-speech taggers and dependency parsers to dialog systems or sentiment … of annotations (abbreviations: T=tokenization, POS=part-of-speech tagging, L=lemmatization, DP=dependency pars- ing, NER=Named Entity Recognition). … Related articles All 4 versions

A Large Scale Database of Strongly-related Events in Japanese. T Shibata, S Kohama, S Kurohashi – LREC, 2014 – lrec-conf.org … i.kyoto-u.ac.jp Abstract The knowledge about the relation between events is quite useful for coreference resolution, anaphora resolution, and several NLP applications such as dialogue system. This paper presents a large scale … Cited by 1 Related articles All 3 versions

Extraction of salient sentences from labelled documents M Denil, A Demiraj, N de Freitas – arXiv preprint arXiv:1412.6815, 2014 – arxiv.org … Bordes et al., 2014; Weston et al., 2014), dialogue systems (Kalchbrenner & Blunsom, 2013b), sentiment analysis (Socher et al., 2011; 2012; Hermann & Blunsom, 2013), and other natural language processing tasks such as chunking and named entity recognition (Collobert et … Cited by 9 Related articles All 4 versions

Learning a Lexicon for Broad-Coverage Semantic Parsing JF Allen – ACL 2014, 2014 – aclweb.org … These include the Stanford tools for POS tagging, named entity recognition and syntactic parsing. … Proc. AAAI (AAAI-2011), pages 859–865 Dzikovska, M., JF Allen, et al.(2008).” Linking Semantic and Knowledge Representation in a Multi-Domain Dialogue System.” Logic and … Cited by 2 Related articles All 12 versions

Metaphor detection with cross-lingual model transfer YTLBA Gershman, ENC Dyer – Proceedings of ACL, Baltimore, …, 2014 – researchgate.net … tion, machine translation, dialog systems, senti- ment analysis, and text analytics, etc.) would have access to a potentially useful high-level … capture lex- ical semantic properties and are quite effec- tive features in semantic processing, includ- ing named entity recognition (Turian … Cited by 1 Related articles All 15 versions

Automatic generation of multiple choice questions using dependency-based semantic relations N Afzal, R Mitkov – Soft Computing, 2014 – Springer … question generation has the potential to be employed in various areas such as intelligent tutoring systems, dialogue systems (Walker et al. … Their approach mainly relied on parse tree manipulation, named entity recognition and Up-keys (significant phrases in a document) to … Cited by 4 Related articles All 4 versions

A Semantic Framework for Harvesting Vague Enterprise Knowledge from Microposts P Alexopoulos, J Pavlopoulos… – International Journal on …, 2014 – World Scientific … As we will explain in the next section, the Named Entity Recognition capabilities of the platform enable the detection of vague ontological statements and assertions 1440008-10 Page 11. … isRelevantToResearchArea PARLANCE Dialogue Systems … Related articles All 8 versions

Computational Discourse Analysis M Dascalu – Analyzing Discourse and Text Complexity for Learning …, 2014 – Springer … Once the pre-processing of a given text is completed (splitting, tokenizing, part of speech tagging, parsing, named entity recognition, co-reference resolution) (Manning and Schütze 1999), the disambiguation graph (see Figure 9) can be built in linear time (Galley and McKeown … Related articles

Unsupervised Active Learning of CRF Model for Cross-Lingual Information Extraction MFA Hady, A Karali, E Kamal, R Ibrahim – International Journal of …, 2014 – gelbukh.com … KEYWORDS: Information extraction, named entity recognition, cross-lingual domain adaptation, unsupervised active learning. … Kim, S., Toutanova, K., Yu, H.: Multilingual named entity recognition us- ing parallel data and metadata from Wikipedia. … Related articles All 4 versions

Part-of-speech tagging in written slang V Korolainen – 2014 – jyx.jyu.fi … FIGURE 1: Architecture pipeline for a Spoken Dialogue System….. … CRF Conditional Random Fields HCI Human-Computer Interaction HMM Hidden Markov Model MEHMM Maximum-Entropy Hidden Markov Model NER Named Entity Recognition NLP Natural … Related articles

Extraction of non-taxonomic relations from texts to enrich a basic ontology M Ribeiro – 2014 – fenix.tecnico.ulisboa.pt … 8 2 Related Work 9 2.1 Named Entity Recognition . . . . . 10 … 16 2.1.4 Summarizing Named Entity Recognition Systems . . . . . 18 2.2 Relation Extraction . . . . . … Related articles All 2 versions

[BOOK] Text Mining of Web-based Medical Content J Bellika, A Bravo-Salgado, M Brezovan, DD Burdescu… – 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 … Cited by 1 Related articles All 4 versions

Incorporating Weak Statistics for Low-Resource Language Modeling S Novotney – 2014 – jscholarship.library.jhu.edu Page 1. Incorporating Weak Statistics for Low-Resource Language Modeling by Scott Novotney A dissertation submitted to The Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy. Baltimore, Maryland February, 2014 … Related articles All 2 versions

Cross-Domain and Cross-Language Porting of Shallow Parsing E Stepanov – 2014 – eprints-phd.biblio.unitn.it Page 1. PhD Dissertation International Doctorate School in Information and Communication Technologies DISI – University of Trento Cross-Domain and Cross-Language Porting of Shallow Parsing Evgeny A. Stepanov Advisor: Prof. Dr. Ing. Giuseppe Riccardi … Related articles

[BOOK] META-NET Strategic Research Agenda for Multilingual Europe 2020 G Rehm, H Uszkoreit – 2014 – dl.pgu.ac.ir … ‚ Information access and management. Example: Information retrieval. ‚ Communication between humans and between humans and machines. Example: Spoken dialogue system. ‚ Translation of spoken and written content. Example: Document translation. … Cited by 14 Related articles All 3 versions

[BOOK] Natural language processing with Java and LingPipe Cookbook B Baldwin, K Dayanidhi – 2014 – books.google.com … He worked on restricted domainspoken dialog systems for Tamil, Telugu, and Hindi in collaboration with IIIT, Hyderabad. … Rahman has publications in major NLP conferences with over 200 citations.He has also worked on other NLPproblems: Named Entity Recognition, Part of … Cited by 1 Related articles All 2 versions

Towards Modeling Collaborative Task Oriented Multimodal Human-human Dialogues L Chen – 2014 – indigo.uic.edu … SmartKom (Wahlster, 2006) was another influen- tial multimodal dialogue systems. SmartKom was a mixed-initiative dialogue system with … Also, most of these coref- erence resolution systems are highly dependent on named entity recognition results. … Cited by 1 Related articles All 4 versions

SongRecommend: From summarization to recommendation S Tata, B Di Eugenio – Natural Language Engineering, 2014 – Cambridge Univ Press … ways, even in the same review – eg, see Song that Jane for The Song that Jane Likes in Figure 1. In addition, song titles need not be noun phrases (NPs) – eg, Ants Marching, Recently – and hence they cannot be extracted with Named Entity Recognition techniques, which … Cited by 3 Related articles All 5 versions

Artificial conversations for chatter bots using knowledge representation, learning, and pragmatics C Chakrabarti – 2014 – repository.unm.edu … 22 2.2 The Syntactic Approach . . . . . 26 2.3 The Semantic Approach . . . . . 27 2.4 Dialogue systems . . . . . 27 viii Page 9. Contents 2.5 Limitations of existing approaches . . . . . 29 … Cited by 3 Related articles All 5 versions

Automated Customer Support With Conversational Agents Employing Text Mining MM NGEA – 2014 – erepository.uonbi.ac.ke … The paper demonstrated the automatic creation of dialog systems to be used in customer care (Feng et al., … contain complex multi –word terms. Named-entity recognition: This identifies the textual information in a document relating the …

Automated Customer Support With Conversational Agents Employing Text Mining: A Case of online University Application MN Munyiva – 2014 – erepository.uonbi.ac.ke … The paper demonstrated the automatic creation of dialog systems to be used in customer care (Feng et al., … contain complex multi –word terms. Named-entity recognition: This identifies the textual information in a document relating the … Related articles

Representation and Processing of Composition, Variation and Approximation in Language Resources and Tools A Savary – 2014 – hal.archives-ouvertes.fr … 74 4.2.1 Named Entity Annotation . . . . . 75 4.2.2 Named Entity Recognition and Classification . . . . . 77 4.2.3 Lexical and Semantic Resources for Named Entities . . . . . … Cited by 1 Related articles All 4 versions

Ontology-based interpretation of natural language P Cimiano, C Unger, J McCrae – Synthesis Lectures on …, 2014 – morganclaypool.com … 2010 Page 7. v Spoken Dialogue Systems Kristiina Jokinen and Michael McTear 2009 Introduction to Chinese Natural Language Processing Kam-Fai Wong, Wenjie Li, Ruifeng Xu, and Zheng-sheng Zhang 2009 Introduction … Cited by 18 Related articles All 5 versions

Foundations and Trends® in Signal Processing L Deng, Y Dong – Signal Processing, 2014 – research.microsoft.com Page 1. the essence of knowledge FnT SIG 7:3-4 Deep Learning; Methods and Applications Li Deng and Dong Y u Foundations and Trends® in Signal Processing 7:3-4 Deep Learning Methods and Applications Li Deng and Dong Yu now now Page 2. 7.1. … Cited by 3 Related articles All 15 versions

Domain-sensitive topic management in a modular conversational agent framework D Macias Galindo – 2014 – researchbank.rmit.edu.au … Building Modular Knowledge Bases for Conversational Agents. In IJCAI Workshop on Knowledge Representation and Reasoning for Practical Dialogue Systems (KRPDS), pages 16–23, Barcelona, Spain, 2011a (ERA Rank: Unranked) … Related articles All 2 versions

Automatically generating reading lists JG Jardine – … of Cambridge, Computer Laboratory, Technical Report, 2014 – cl.cam.ac.uk Page 1. Technical Report Number 848 Computer Laboratory UCAM-CL-TR-848 ISSN 1476-2986 Automatically generating reading lists James G. Jardine February 2014 15 JJ Thomson Avenue Cambridge CB3 0FD United Kingdom phone +44 1223 763500 … Cited by 2 Related articles All 6 versions

Topical Structure in Long Informal Documents A Kazantseva – 2014 – ruor.uottawa.ca … informative, alternative. To date, models based on topical segments have been used in information extraction, essay analysis and scoring, automatic assessment of coherence of text, automatic dialogue systems, etc. [Webber et al., 2012]. On the other side of the issue … Cited by 1 Related articles All 11 versions

Morphological Analysis of Ge’ez Verbs Using Memory Based Learning Y Abate – 2014 – etd.aau.edu.et Page 1. 1 ADDIS ABABA UNIVERSITY SCHOOL OF GRADUATE STUDIES DEPARTMENT OF COMPUTER SCIENCE Morphological Analysis of Ge’ez Verbs Using Memory Based Learning Yitayal Abate A THESIS SUBMITTED … Related articles

Performance Stylistics K O’Halloran – Digital Literary Studies: Corpus Approaches to …, 2014 – books.google.com Page 161. 7 Performance Stylistics Deleuze and Guattari, Poetry, and (Corpus) Linguistics Kieran O’Halloran 7.1 INTRODUCTION 7.1. 1 Orientation A common approach to reading a poem is initially to ask “what is this poem … Related articles