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Read e-book online Word Sense Disambiguation: Algorithms and Applications PDF

By Associate Professor Eneko Agirre (auth.), Associate Professor Eneko Agirre, Research Scientist Philip Edmonds (eds.)

ISBN-10: 1402048084

ISBN-13: 9781402048081

ISBN-10: 1402048092

ISBN-13: 9781402048098

This is the 1st ebook to hide the total subject of observe feel disambiguation (WSD) together with: the entire significant algorithms, thoughts, functionality measures, effects, philosophical matters, and purposes. top researchers within the box have contributed chapters that synthesize and supply an outline of previous and state of the art examine around the box. The editors have rigorously equipped the chapters into sub-topics. Researchers and teachers will know about the entire diversity of what has been performed and the place the sphere is headed. builders will study which technique(s) will observe to their specific program, tips on how to construct and assessment structures, and what functionality to count on. An accompanying site (www.wsdbook.org) offers hyperlinks to assets for WSD and a searchable index of the book.

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Extra resources for Word Sense Disambiguation: Algorithms and Applications

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How to divide senses still remains one of the main open problems of WSD. As discussed in this chapter and throughout the book (see especially Chaps. 2, 3, and 4), semantic granularity is not well understood, and the relation to specific applications is unexplored territory. Given the state of the art, coarse-grained differences could allow for performance closer to an application’s needs. Evaluation. The first Senseval was held at about the time Ide and Véronis (1998) was published. As mentioned above, Senseval’s common evaluation framework has focused research, enabled scientific rigor, and generated substantial resources.

2005. Word sense disambiguation vs. statistical machine translation. Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL), Ann Arbor, Michigan, 387–394. Chapman, Robert. 1977. Roget’s International Thesaurus (Fourth Edition). New York: Harper and Row. Chlovski, Timothy & Rada Mihalcea. 2002. Building a sense tagged corpus with Open Mind Word Expert. Proceedings of the Workshop on Word Sense Disambiguation: Recent Successes and Future Directions, Philadelphia, PA, USA, 116–122.

WSD as an Optimization Problem. Current WSD systems disambiguate texts one word at a time, treating each word in isolation. It is clear though that meanings are interdependent and the disambiguation of a word can affect others in its context. , Lesk (1986) and Cowie et al. (1992)). The interdependencies among senses in the context could be modeled and treated as an optimization problem (in contrast to the classification model of WSD). Applying Deeper Linguistic Knowledge. Significant advances in the performance of current supervised WSD systems could rely on enriched feature representations based on deeper linguistic knowledge, rather than better learning algorithms.

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Word Sense Disambiguation: Algorithms and Applications by Associate Professor Eneko Agirre (auth.), Associate Professor Eneko Agirre, Research Scientist Philip Edmonds (eds.)


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