NDLI: Clustering for Web information hierarchy mining

Content Provider	IEEE Xplore Digital Library
Author	Hung-Yu Kao Ming-Syan Chen Jan-Ming Ho
Copyright Year	2003
Description	Author affiliation: Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan (Hung-Yu Kao; Ming-Syan Chen)
Abstract	Benefiting from the growth of techniques of dynamic page generation, the amount and the complexity of Web pages increase explosively. The structures of Web pages which are dynamically generated by the same templates are thus similar to one another and are usually assembled by a set of fundamental information clusters These neighboring information clusters usually represent the similar semantics and form a larger cluster with the more generalized information. The hierarchical structure generated by information clusters in a bottom-up manner is called the information hierarchy of a page. We study the problem of mining the information hierarchies of pages in Web sites to recognize the information distribution of pages within the multilevel, multigranularity configurations. Explicitly, we propose an information clustering system that applies a top-down information centroid searching algorithm and a multigranularity centroid converging process on the document object model (DOM) trees of pages to build the information hierarchies of pages. Experiments on several real news Web sites show the high precision and recall rates of the proposed method on determining information clusters of pages and also validate its practical applicability to real Web sites.
Sponsorship	IEEE Comput. Soc. Tech. Committee on Computational Intelligence (TCCI) Web Intelligence Consortium (WIC)
Starting Page	698
Ending Page	701
File Size	351706
Page Count	4
File Format	PDF
ISBN	0769519326
DOI	10.1109/WI.2003.1241299
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-10-13
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Information science Scalability Merging Web pages Clustering algorithms HTML Electronic mail Data mining Joining processes Assembly
Content Type	Text
Resource Type	Article

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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ClusTex: Information Extraction from HTML Pages

Feedback-driven clustering for automated linking of web pages

Approximate ontology merging for the semantic Web

Building Web Information Extraction Tasks

Application of layered clustering and plane partition in Web page classification

Automatic contour segmentation for object analysis

Data Extraction from Semi-structured Web Pages by Clustering

Web mining based on VIPS in intention-based information retrieval

Hybrid clustering with application to Web mining

Clustering for Web information hierarchy mining

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ClusTex: Information Extraction from HTML Pages

Feedback-driven clustering for automated linking of web pages

Approximate ontology merging for the semantic Web

Building Web Information Extraction Tasks

Application of layered clustering and plane partition in Web page classification

Automatic contour segmentation for object analysis

Data Extraction from Semi-structured Web Pages by Clustering

Web mining based on VIPS in intention-based information retrieval

Hybrid clustering with application to Web mining

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