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Open-Domain Question Answering from Large Text Collections
Contributor(s): Pasca, Marius (Author)
ISBN: 1575864274     ISBN-13: 9781575864273
Publisher: Center for the Study of Language and Informat
OUR PRICE:   $69.30  
Product Type: Hardcover
Published: April 2003
Qty:
Temporarily out of stock - Will ship within 2 to 5 weeks
Annotation: Many books have indexes, but most textual media have none. Newspapers, legal transcripts, conference proceedings, correspondence, video subtitles, and web pages are increasingly accessible with computers, yet are still without indexes or other sophisticated means of finding the excerpts most relevant to a reader's question.
Better than an index, and much better than a keyword search, are the high-precision computerized question-answering systems explored in this book. Marius Pasca presents novel and robust methods for capturing the semantics of natural language questions and for finding the most relevant portions of texts. This research has led to a fully implemented and rigorously evaluated architecture that has produced experimental results showing great promise for the future of internet search technology.

Additional Information
BISAC Categories:
- Language Arts & Disciplines | Linguistics - General
Dewey: 410.285
LCCN: 2002155954
Series: Studies in Computational Linguistics
Physical Information: 0.59" H x 6.06" W x 9.52" (0.77 lbs) 157 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
Many books have indexes, but most textual media have none. Newspapers, legal transcripts, conference proceedings, correspondence, video subtitles, and web pages are increasingly accessible with computers, yet are still without indexes or other sophisticated means of finding the excerpts most relevant to a reader's question.

Better than an index, and much better than a keyword search, are the high-precision computerized question-answering systems explored in this book. Marius Pasca presents novel and robust methods for capturing the semantics of natural language questions and for finding the most relevant portions of texts. This research has led to a fully implemented and rigorously evaluated architecture that has produced experimental results showing great promise for the future of internet search technology.