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Automated metadata and instance extraction from news Web sites

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4 Author(s)
Srinivas Vadrevu ; Dept. of Comput. Sci. & Eng., Arizona State Univ., Tempe, AZ, USA ; Saravanakumar Nagarajan ; Fatih Gelgi ; Hasan Davulcu

Over the past few years World Wide Web has established as a vital resource for news. With the continuous growth in the number of available news Web sites and the diversity in their presentation of content, there is an increasing need to organize the news related information on the Web and keep track of it. In this paper, we present automated techniques for extracting metadata instance information by organizing and mining a set of news Web sites. We develop algorithms that detect and utilize HTML regularities in the Web documents to turn them into hierarchical semantic structures encoded as XML. The tree-mining algorithms that we present identify key domain concepts and their taxonomical relationships. We also extract semi-structured concept instances annotated with their labels whenever they are available. We report experimental evaluation for the news domain to demonstrate the efficacy of our algorithms.

Published in:

The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05)

Date of Conference:

19-22 Sept. 2005