Information Extraction: Algorithms and Prospects in a by Marie-Francine Moens

By Marie-Francine Moens

Details extraction regards the procedures of structuring and mixing content material that's explicitly said or implied in a single or a number of unstructured details assets. It contains a semantic type and linking of sure items of data and is taken into account as a mild type of content material figuring out by way of the laptop. at present, there's a substantial curiosity in integrating the result of info extraction in retrieval structures, due to the transforming into call for for se's that go back specified solutions to versatile info queries. complex retrieval types fulfill that desire they usually depend on instruments that instantly construct a probabilistic version of the content material of a (multi-media) document.The publication specializes in content material acceptance in textual content. It elaborates at the previous and present so much winning algorithms and their software in various domain names (e.g., information filtering, mining of biomedical textual content, intelligence accumulating, aggressive intelligence, criminal details looking out, and processing of casual text). a tremendous half discusses present statistical and desktop studying algorithms for info detection and category, and integrates their leads to probabilistic retrieval types. The e-book additionally unearths a couple of rules in the direction of a complicated knowing and synthesis of text. The ebook is geared toward researchers and software program builders attracted to info extraction and retrieval, however the many illustrations and actual global examples make it additionally appropriate as a instruction manual for college kids.

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Extra resources for Information Extraction: Algorithms and Prospects in a Retrieval Context: Algorithms and Prospects in a Retrieval Context

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2003. ). New Directions in Question Answering. In Papers from the 2003 AAAI Spring Symposium. Menlo Park, CA: The AAAI Press. Moens, Marie-Francine (2002). What information retrieval can learn from casebased reasoning. In Proceedings JURIX 2002: The Fifteenth Annual Conference (Frontiers in Artificial Intelligence and Applications) (pp. 83-91). Amsterdam: IOS Press. Moens, Marie-Francine (2003). Interrogating legal documents: The future of legal information systems? In Proceedings of the JURIX 2003 Workshop on Question Answering for Interrogating Legal Documents December 11, 2003 (pp.

Apple is a hyponym of fruit). , leg is a part off body). The relations here discussed can be found in a lexico-semantic resource such as WordNet for English (Miller 1990). Other lexico-semantic resources such as FrameNett are valuable. , 1998; Fillmore and Baker, 2001). The aim is to document the range of semantic and syntactic combinatory possibilities (valences) of each word in each of its senses, through computer assisted annotation of example sentences and automatic tabulation and display of the annotation results.

Strict synonymy almost never occurs, since word forms describing the same concept tend to differentiate their meanings. , an obnoxious sound) whereas the meaning of 30 2 Information Extraction from an Historical Perspective sound is neutral. , tree is a hypernym of oak). , apple is a hyponym of fruit). , leg is a part off body). The relations here discussed can be found in a lexico-semantic resource such as WordNet for English (Miller 1990). Other lexico-semantic resources such as FrameNett are valuable.

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