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Discovery of Concept Entities from Web Sites using Web Unit Mining.

by Ming Yin, Dion Hoe-Lian Goh, Ee-Peng Lim, Aixin Sun
IJWIS ()
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Abstract

This paper presents a novel method for extracting information from collections of Web pages across different sites. Our method uses a standard wrapper induction algorithm and exploits named entity information. We introduce the idea of post-processing the extraction results for resolving ambiguous facts and improve the overall extraction performance. Postprocessing involves the exploitation of two additional sources of information: fact transition probabilities, based on a trained bigram model, and confidence probabilities, estimated for each fact by the wrapper induction system. A multiplicative model that is based on the product of those two probabilities is also considered for post-processing. Experiments were conducted on pages describing laptop products, collected from many different sites and in four different languages. The results highlight the effectiveness of our approach.

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Authors on Mendeley

  1. Aixin Sun
    Associate Professor
    Nanyang Technological University

Readership Statistics

7 Readers on Mendeley
by Discipline
 
57% Computer Science
 
14% Business, Management and Accounting
 
14% Linguistics
by Academic Status
 
43% Student > Ph. D. Student
 
14% Professor > Associate Professor
 
14% Researcher
by Country
 
29% Portugal
 
14% India
 
14% Russia

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