Welcome to DiSC 2003
SIGMOD 2002
PODS 2002
SIGMOD RECORD 2002
ADBIS 2002
CIKM 2002
= CIKM'02 Website
<<< = CIKM'02 Papers>>>
= CIKM Workshop_1
= GIS'02 Papers
= CIKM Workshop_2
= DOLAP'02 Papers
= CIKM Workshop_3
= WIDM'02 Papers
CoopIS 2002
EDBT 2002
ER 2002
Data Engineering Bul
DEXA_EC-WEB 2002
DMKD 2002
DPDJ 2002
HYPERTEXT 2002
ICDE 2002
ICDM 2002
JCDL 2002
KDD 2002
KDD_EXPLORATIONS 20
KRDB 2002
MDM 2002
MIS 2002
RIDE 2002
SBBD 2002
SIGIR 2002
SIGIR FORUM 2002
SSDBM 2002
TODS 2002
TIME 2002
VLDB 2002
VLDBJ 2002

Entropy-based link analysis for mining web informative structures


Hung-Yu Kao, Ming-Syan Chen, Shian-Hua Lin, and Jan-Ming Ho

  View Paper (PDF)  

Return to Web search 2


Abstract

In this paper, we study the problem of mining the informative structure of a news Web site which consists of thousands of hyperlinked documents. We define the informative structure of a news Web site as a set of index pages (or referred to as TOC, i.e., table of contents, pages) and a set of article pages linked by TOC pages through informative links. It is noted that the Hyperlink Induced Topics Search (HITS) algorithm has been employed to provide a solution to analyzing authorities and hubs of pages. However, most of the content sites tend to contain some extra hyperlinks, such as navigation panels, advertisements and banners, so as to increase the add-on values of their Web pages. Therefore, due to the structure induced by these extra hyperlinks, HITS is found to be insufficient to provide a good precision in solving the problem. To remedy this, we develop an algorithm to utilize entropy-based Link Analysis on Mining Web Informative Structures. This algorithm is referred to as LAMIS. The key idea of LAMIS is to utilize information entropy for representing the knowledge that corresponds to the amount of information in a link or a page in the link analysis. Experiments on several real news Web sites show that the precision and the recall of LAMIS are much superior to those obtained by heuristic methods and conventional ink analysis methods.


DiSC'03 © 2003 Association for Computing Machinery