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Improving topic tracking using domai...

Yang, Li.

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Improving topic tracking using domain chaining.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Improving topic tracking using domain chaining./
Author:	Yang, Li.
Description:	102 p.
Notes:	Source: Masters Abstracts International, Volume: 42-04, page: 1123.
Contained By:	Masters Abstracts International42-04.
Subject:	Language, Linguistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1418461

Improving topic tracking using domain chaining.
Yang, Li.

Improving topic tracking using domain chaining. - 102 p.

Source: Masters Abstracts International, Volume: 42-04, page: 1123.

Thesis (M.A.)--University of North Texas, 2003.

Topic Detection and Tracking (TDT) research has produced some successful statistical tracking systems. While lexical chaining, a non-statistical approach, has also been applied to the task of tracking by Carthy and Stokes for the 2001 TDT evaluation, an efficient tracking system based on this technology has yet to be developed. In thesis we investigate two new techniques which can improve Carthy's original design.Subjects--Topical Terms:

1018079
Language, Linguistics.

Improving topic tracking using domain chaining.
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035 $a (UnM)AAI1418461
035 $a AAI1418461
040 $a UnM $c UnM
100 1 $a Yang, Li. $3 1029288
245 1 0 $a Improving topic tracking using domain chaining.
300 $a 102 p.
500 $a Source: Masters Abstracts International, Volume: 42-04, page: 1123.
500 $a Major Professor: Timothy Montler.
502 $a Thesis (M.A.)--University of North Texas, 2003.
520 $a Topic Detection and Tracking (TDT) research has produced some successful statistical tracking systems. While lexical chaining, a non-statistical approach, has also been applied to the task of tracking by Carthy and Stokes for the 2001 TDT evaluation, an efficient tracking system based on this technology has yet to be developed. In thesis we investigate two new techniques which can improve Carthy's original design.
520 $a First, at the core of our system is a semantic domain chainer. This chainer relies not only on the WordNet database for semantic relationships but also on Magnini's semantic domain database, which is an extension of WordNet. The domain-chaining algorithm is a linear algorithm. Second, to handle proper nouns, we gather all of the ones that occur in a news story together in a chain reserved for proper nouns.
520 $a In this thesis we also discuss the linguistic limitations of lexical chainers to represent textual meaning.
590 $a School code: 0158.
650 4 $a Language, Linguistics. $3 1018079
650 4 $a Computer Science. $3 626642
690 $a 0290
690 $a 0984
710 2 0 $a University of North Texas. $3 1017396
773 0 $t Masters Abstracts International $g 42-04.
790 1 0 $a Montler, Timothy, $e advisor
790 $a 0158
791 $a M.A.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1418461