Download PDF by Tomek Strzalkowski, Sanda Harabagiu: Advances in Open Domain Question Answering (Text, Speech and

By Tomek Strzalkowski, Sanda Harabagiu

ISBN-10: 1402047444

ISBN-13: 9781402047442

ISBN-10: 1402047460

ISBN-13: 9781402047466

This new Springer quantity offers a finished and specific examine present techniques to automatic query answering. the extent of presentation is acceptable for rookies to the sector in addition to for execs wishing to review this sector and/or to construct useful QA platforms. The e-book can function a "how-to" instruction manual for IT practitioners and method builders. it will possibly even be used to coach graduate classes in machine technology, info technological know-how and similar disciplines.

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Extra resources for Advances in Open Domain Question Answering (Text, Speech and Language Technology)

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Similar to the above issue, a question may refer to the subject/object in an abbreviated form, while the answer will refer to the subject/object in its full, proper form. ”, Microsoft is referred to as Microsoft Corp. An axiom is built such that each noun of the complex nominal takes on the identifying argument of the complex nominal: ƒ all x1 x2 x3 (microsoft_nn(x1) & corp_nn(x2) & nn_nnc(x3,x1,x2) → microsoft_nn(x3) & corp_nn(x3)) Similar axioms are used for coordinated conjunctions detected in the answer and the question.

We limited our evaluation set to 100 questions only due to the complexity of the evaluation process, which required human verification for all image answers. The system was configured to report the top 10 answers found for SOME ADVANCED FEATURES OF LCC’S POWERANSWER 31 each question. For each answer position we have extracted the sentence answer, which consists of the sentence where the textual answer is located, the exact answer, which is only the text snippet that contains the actual answer, and the image answer which is the multimedia object associated with the textual answer.

SOME ADVANCED FEATURES OF LCC’S POWERANSWER 23 5. 1 Motivation The design of complex algorithms and the addition of advanced features to stateof-the-art QA systems lead to the goal of extracting more accurate answers from large document collections. The previous sections are concrete illustrations in this sense. But regardless of the complexity of the techniques used for answer finding, the range of questions with potentially correct answers is still limited by the contents of the collection. In principle, the larger and more diverse the document collection, the wider the range of questions for which relevant information exists in the collection.

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


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