Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/91291
Title: On discovering concept entities from web sites
Authors: Yin, Ming
Goh, Dion Hoe-Lian
Lim, Ee Peng
Keywords: DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks
Issue Date: 2005
Source: Yin, M., Goh, D., & Lim, E. P. (2005). On discovering concept entities from web sites. Proceedings of the International Conference on Computational Science and its Applications 2005 ICCSA 2005, (May 9-12, Singapore), Lecture Notes in Computer Science 3481, 1177- 1186.
Abstract: A web site usually contains a large number of concept entities, each consisting of one or more web pages connected by hyperlinks. In order to discover these concept entities for more expressive web site queries and other applications, the web unit mining problem has been proposed. Web unit mining aims to determine web pages that constitute a concept entity and classify concept entities into categories. Nevertheless, the performance of an existing web unit mining algorithm, iWUM, suffers as it may create more than one web unit (incomplete web units) from a single concept entity. This paper presents a new web unit mining algorithm, kWUM, which incorporates site-specific knowledge to discover and handle incomplete web units by merging them together and assigning correct labels. Experiments show that the overall accuracy has been significantly improved.
URI: https://hdl.handle.net/10356/91291
http://hdl.handle.net/10220/6122
DOI: http://dx.doi.org/10.1007/11424826_125
Rights: The original publication is available at www.springerlink.com.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:WKWSCI Conference Papers

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