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Found 463 results
[ Author(Desc)] Title Type Year
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Mollá D, Hutchinson B.  2003.  Intrinsic versus extrinsic evaluations of parsing systems. Proceedings of the EACL 2003 Workshop on Evaluation Initiatives in Natural Language Processing: are evaluation methods, metrics and resources reusable?. :43–50.
Mollá D.  2006.  Learning of graph-based question answering rules. First Workshop on Graph Based Methods for Natural Language Processing. :37–44.
Mollá D.  2005.  Sistemas de Búsqueda de Respuestas.
Mollá D, Hutchinson B.  2002.  Dependency-Based Semantic Interpretation for Answer Extraction. 2002 Australasian NLP Workshop.
Mollá D, van Zaanen M.  2006.  AnswerFinder at TREC 2005. The Fourteenth Text REtrieval Conference (TREC 2005).
Mollá D, Wan S.  2006.  Macquarie University at DUC 2006: Question Answering for Summarisation. Document Understanding Conference (DUC).
Mollá D, Gardiner M.  2004.  Answerfinder - question answering by combining lexical, syntactic and semantic information. Australasian Language Technology Workshop (ALTW) 2004. :9–16.
Morneau M, Mineau GW, Corbett D.  2006.  SeseiOnto: Interfacing NLP and Ontology Extraction. IEEE/WIC/ACM International Conference on Web Intelligence. :449–455.
Morneau M, Mineau GW.  2008.  Employing a Domain Specific Ontology to Perform Semantic Search. Conceptual Structures: Knowledge Visualization and Reasoning. 5113:242-254.
Morneau M, Mineau GW, Corbett D.  2006.  Using an automatically generated ontology to improve information retrieval. First Conceptual Structures Tool Interoperability Workshop (CS-TIW 2006).
Moshfeghi Y, Jose JM.  2013.  On the effectiveness of emotion extraction techniques. 10th Conference on Open Research Areas in Information Retrieval.
Moshfeghi Y.  2012.  Role of emotion in information retrieval. School of Computing Science, College of Science and Engineering. PhD
Muñoz R, Mitkov R, Palomar M, Peral J, Evans R, Moreno L, Orăsan C, Saiz-Noeda M, Ferrández A, Barbu C et al..  2002.  Bilingual alignment of anaphoric expressions. The Third International Conference on Language Resources and Evaluation (LREC).
Mutton A, Dras M, Wan S, Dale R.  2007.  GLEU: Automatic Evaluation of Sentence-Level Fluency. 45th Annual Meeting of the Association of Computational Linguistics.
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Na J-C, Sui H, Khoo C, Chan S, Zhou Y.  2004.  Effectiveness of Simple Linguistic Processing in Automatic Sentiment Classification of Product Reviews. Knowledge Organization and the Global Information Society: Proceedings of the Eighth International ISKO Conference. :49-54.
Nagy Á.  2012.  Contrasting French nominal terms to common language NPs – towards a rule-based term extractor. First Central European Conference in Linguistics for postgraduate Students .
Neviarouskaya A, Prendinger H, Ishizuka M.  2010.  AM: textual attitude analysis model. NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text. :80–88.
Neviarouskaya A, Prendinger H, Ishizuka M.  2015.  Attitude Sensing in Text Based on A Compositional Linguistic Approach. Computational Intelligence. 31:256–300.
Neviarouskaya A, Prendinger H, Ishizuka M.  2007.  Analysis of affect expressed through the evolving language of online communication. 12th international conference on Intelligent user interfaces. :278–281.
Neviarouskaya A, Prendinger H, Ishizuka M.  2011.  Affect Analysis Model: novel rule-based approach to affect sensing from text. Natural Language Engineering. 17(1):95-135.
Neviarouskaya A, Prendinger H, Ishizuka M.  2009.  Semantically distinct verb classes involved in sentiment analysis. IADIS International Conference APPLIED COMPUTING 2009.
Neviarouskaya A, Prendinger H, Ishizuka M.  2010.  Recognition of Fine-Grained Emotions from Text: An Approach Based on the Compositionality Principle. Modeling Machine Emotions for Realizing Intelligence. 1:179-207.
Neviarouskaya A, Aono M.  2012.  Analyzing Sentiment Word Relations with Affect, Judgment, and Appreciation. 2nd Workshop on Sentiment Analysis where AI meets Psychology (SAAIP 2012).
Neviarouskaya A, Prendinger H, Ishizuka M.  2009.  Compositionality Principle in Recognition of Fine-Grained Emotions from Text.
Neviarouskaya A, Aono M.  2013.  Extracting Causes of Emotions from Text. International Joint Conference on Natural Language Processing.

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