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Tomek Strzalkowski, Sanda Harabagiu's Advances in Open Domain Question Answering (Text, Speech and PDF

By Tomek Strzalkowski, Sanda Harabagiu

ISBN-10: 1402047444

ISBN-13: 9781402047442

ISBN-10: 1402047460

ISBN-13: 9781402047466

This new Springer quantity presents a complete and specific examine present ways to automatic query answering. the extent of presentation is acceptable for beginners to the sector in addition to for pros wishing to review this zone and/or to construct sensible QA platforms. The e-book can function a "how-to" guide for IT practitioners and process builders. it will possibly even be used to educate graduate classes in machine technological know-how, info technology and similar disciplines.

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Table 5 illustrates relevant answer strings extracted after the WordNet-based automatic expansion of Definition questions. SOME ADVANCED FEATURES OF LCC’S POWERANSWER 15 Extracting Exact Answers Exact answers are extracted after parsing the sentences in which answer patterns or WordNet concepts are found. To this effect, the parse tree of the whole sentence is processed to derive the phrase that gives the exact answer. The exact answer is selected from the enclosing phrase around the question phrase to search.

Similarly, the pattern “NP1 reflect NP2” identified the relation “Influence(NP1, NP2)” from the text “As a rough approximation, at least, nominal interest rates reflect rates of inflation”. New concepts are classified with respect to one another based on the subsumption principle. Each new concept is thus inserted in the correct position into partially built ontologies. This is how ontologies are built iteratively from a variety of document sources as shown in Table 11. In our tests, the sources of the ontology were both Web documents, and a specialized corpus denoted CNS.

The ontology building process has four main steps: discovery of new concepts; discovery of new relationships via lexico-semantic patterns; and classification and integration with a WordNet-like knowledge base (Moldovan and Girju, 2001). Table 11. Illustration of ontologies acquired from local and Web documents. Ontology Doc. source Nr. concepts Max. depth Examples of concepts grenade CNS 92 3 Antipersonnel grenade, carbon tet grenade, frag grenade, incendiary grenade WMD CNS 144 4 terrorist group CNS 143 4 search engine Web 60 3 sports car Web 41 3 Biological weapon, atom bomb, Aryan Nations, ETA, Islamic Jihad, SEndoro Luminoso, Jewish Defense League, Hizballah Fundamentalist terrorist group, Aryan Nation, ETA, Islamic Jihad, Sendoro Luminoso, Jewish Defense League, Hizballah Web search engine, CUSI, AltaVista, Fast, Google, Ixquick, meta search engine British sports cars, 914s, Nissan 300zx, luxury sports car, Ferrari Testarossa The discovery of new concepts starts around some seed concepts that a user considers important for the domain.

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Advances in Open Domain Question Answering (Text, Speech and Language Technology) by Tomek Strzalkowski, Sanda Harabagiu

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