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METEOR: metadata and instance extraction from object referral lists on the web

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METEOR: metadata and instance extraction from object referral lists on the web
The Web has established itself as the largest public data repository ever available. Even though the vast majority of information on the Web is formatted to be easily readable by the human eye, "meaningful information" is still largely inaccessible for the computer applications. In this paper we present the METEOR system which utilizes various presentation and linkage regularities from referral lists of various sorts to automatically separate and extract metadata and instance information. Experimental results for the university domain with 12 computer science department Web sites, comprising 361 individual faculty and course home pages indicate that the performance of the metadata and instance extraction averages 85%, 88% F-measure respectively. METEOR achieves this performance without any domain specific engineering requirement. Categories and Subject Descriptors: H.4.m [Information Systems]: Miscellaneous; I.2.6 [Artificial Intelligence]: Learning? Knowledge Acquisition Ge...
Hasan Davulcu, Srinivas Vadrevu, Saravanakumar Nag
Added 22 Nov 2009
Updated 22 Nov 2009
Type Conference
Year 2005
Where WWW
Authors Hasan Davulcu, Srinivas Vadrevu, Saravanakumar Nagarajan, Fatih Gelgi
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