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

By Tomek Strzalkowski, Sanda Harabagiu

This new Springer quantity presents a entire and designated examine present ways to automatic query answering. the extent of presentation is acceptable for novices to the sector in addition to for execs wishing to check this zone and/or to construct sensible QA platforms. The e-book can function a "how-to" guide for IT practitioners and method builders. it may possibly even be used to educate graduate classes in desktop technological know-how, details technological know-how and similar disciplines.

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

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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. Conversely, the presence of large amounts of text tests the efficiency of the QA system to the limit, calling for lightweight extraction mechanisms based on natural language.

To actually find relevant information, users must read the first documents. Even if relevant information is inside the first hit returned, finding it can still be time-consuming if the document is very long. QA systems act as advanced interfaces for Web searching, permitting users to use natural language and thus concentrate on what they are actually looking for, rather than on the artificial constraints imposed by a particular syntax. Submitting written questions to an answer engine is easier than building an artificial query from a set of keywords organized around various operators.

The system performance on the remaining 76 questions is shown in Table 17. Table 17 shows that the multimedia score is approximately 15% higher than the original score, which indicates that the image extraction performance is almost as good as the accuracy of the textual system for sentence answers. Table 17. Performance over the questions which have image answers in the returned documents. 65 To give an indication about the utility of a multimedia QA system we show some of our favorite textual answers with the corresponding image answers in Table 18.

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