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Found 463 results
[ Author(Desc)] Title Type Year
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A. Neviarouskaya, Prendinger, H., and Ishizuka, M., Attitude Sensing in Text Based on A Compositional Linguistic Approach, Computational Intelligence, vol. 31, pp. 256–300, 2015.
A. Neviarouskaya, Prendinger, H., and Ishizuka, M., Analysis of affect expressed through the evolving language of online communication, in 12th international conference on Intelligent user interfaces, New York, NY, USA, 2007, pp. 278–281.
A. Neviarouskaya, Prendinger, H., and Ishizuka, M., Affect Analysis Model: novel rule-based approach to affect sensing from text, Natural Language Engineering, vol. 17, no. 1, pp. 95-135, 2011.
A. Neviarouskaya, Prendinger, H., and Ishizuka, M., Semantically distinct verb classes involved in sentiment analysis, in IADIS International Conference APPLIED COMPUTING 2009, Rome, Italy, 2009.
A. Neviarouskaya, Prendinger, H., and Ishizuka, M., Recognition of Fine-Grained Emotions from Text: An Approach Based on the Compositionality Principle, in Modeling Machine Emotions for Realizing Intelligence, vol. 1, R. J. Howlett, Jain, L. C., Nishida, T., Jain, L. C., and Faucher, C. Berlin Heidelberg: Springer, 2010, pp. 179-207.
A. Neviarouskaya and Aono, M., Analyzing Sentiment Word Relations with Affect, Judgment, and Appreciation, in 2nd Workshop on Sentiment Analysis where AI meets Psychology (SAAIP 2012), Mumbai, 2012.
J. Nivre, Dependency grammar and dependency parsing, Växjö University, 2005.
J. Nivre, What kinds of trees grow in Swedish soil? A comparison of four annotation schemes for Swedish, in First Workshop on Treebanks and Linguistic Theories (TLT2002), Sozopol, Bulgaria, 2002.
J. Nivre, Inductive Dependency Parsing. Dordrecht: Springer, 2006, p. 216.
K. Nyberg, Raiko, T., Tiinanen, T., and Hyvönen, E., Document classification utilising ontologies and relations between documents, in Eighth Workshop on Mining and Learning with Graphs, 2010, pp. 86–93.
E. Nyberg, Riebling, E., Wang, R. C., and Frederking, R., Integrating a Natural Language Message Pre-Processor with UIMA, 2008.
K. Nyberg, Document Classification Using Machine Learning and Ontologies, Aalto University, Espoo, 2011.
F. Olsson, Bootstrapping Named Entity Annotation by Means of Active Machine Learning, University of Gothenburg, 2008.
C. Orăsan and Puşcaşu, G., A High Precision Information Retrieval Method for WiQA, in Evaluation of Multilingual and Multi-modal Information Retrieval, vol. 4730, C. Peters, Clough, P., Gey, F. C., Karlgren, J., Magnini, B., Oard, D. W., Rijke, M., and Stempfhuber, M. Berlin / Heidelberg: Springer, 2007, pp. 561-568.
C. Orăsan and Evans, R., NP Animacy Identification for Anaphora Resolution, Journal Of Artificial Intelligence Research, vol. 29, pp. 79-103, 2007.
C. Orăsan, Evans, R., and Mitkov, R., Enhancing Preference-Based Anaphora Resolution with Genetic Algorithms, in Natural Language Processing — NLP 2000, vol. 1835, D. N. Christodoulakis Berlin / Heidelberg: Springer, 2000, pp. 185-195.
S. Ou, Khoo, C., and Goh, D. H. - L., Design and development of a concept-based multi-document summarization system for research abstracts, Journal of Information Science, vol. 34, pp. 308-326, 2008.
P. Pääkkö and Lindén, K., Finding a Location for a New Word in WordNet, in Global Wordnet Conference, Matsue, Japan, 2012.
A. Pajunen, Verbisanaston uudistuminen, Puhe ja kieli, vol. 26, no. 4, pp. 205-219, 2006.
A. Pareja-Lora, Enabling automatic, technology-enhanced assessment in language e-learning, in Technology-Enhanced Language Learning for Specialized Domains: Practical Applications and Mobility, E. Martín-Monje, Elorza, I., and Riaza, B. García Routledge, 2016, pp. 102-126.
A. Pareja-Lora, OntoTag - A Linguistic and Ontological Annotation Model Suitable for the Semantic Web, Universidad Politécnica de Madrid, Madrid, 2012.
A. Pareja-Lora and Aguado de Cea, G., Ontology-based interoperation of linguistic tools for an improved lemma annotation in Spanish, in The seventh international conference on Language Resources and Evaluation, LREC 2010, 2010.
A. Pareja-Lora, Using ontologies to interlink linguistic annotations and improve their accuracy, in New perspectives on teaching and working with languages in the digital era, A. Pareja-Lora, Calle-Martínez, C., and Rodríguez-Arancón, P., 2016, pp. 351-362.
Y. C. Park, Kim, P. K., Golshani, F., and Panchanathan, S., Technique for eliminating irrelevant terms in term rewriting for annotated media retrieval, in Proceedings of the ninth ACM international conference on Multimedia, New York, NY, USA, 2001, pp. 582–584.
V. Pekar, Discovery of event entailment knowledge from text corpora, Computer Speech & Language, vol. 22, no. 1, pp. 1 - 16, 2008.