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Relational Model Based Annotation of the Web Data.

Authors :
Kacprzyk, Janusz
Węgrzyn-Wolska, Katarzyna M.
Szczepaniak, Piotr S.
Gelgi, Fatih
Vadrevu, Srinivas
Davulcu, Hasan
Source :
Advances in Intelligent Web Mastering; 2007, p124-129, 6p
Publication Year :
2007

Abstract

In this paper, we present a fast and scalable Bayesian model for improving weakly annotated data — which is typically generated by a (semi) automated information extraction (IE) system from Web documents. Weakly annotated data suffers from incorrect ontological role assignments. Our experimental evaluations with the TAP and a collection of 20,000 home pages from university, shopping and sports Web sites, indicate that the model described here can improve the accuracy of role assignments from 40% to 85% for template driven sites, from 68% to 87% for non-template driven sites. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540725749
Database :
Supplemental Index
Journal :
Advances in Intelligent Web Mastering
Publication Type :
Book
Accession number :
33094082
Full Text :
https://doi.org/10.1007/978-3-540-72575-6_20