A New Algorithm To Measure Relevance Among
Web Pages
Author(s)
M. S. Sadi, M. M. H. Rahman & S. Horiguchi
Abstract
This paper proposes a new algorithm to measure relevance among Web pages
(RWP) using a hybrid method of hyperlink analysis and content analysis. Here we
used a new approach to Web searching where the input to the search process is
not a set of query terms, rather the URL of a page, and the output is a set of
related Web pages. A related Web page is one that addresses the same topic as the
original page. Here, the proposed algorithm first uses only the connectivity
information in the Web (i.e., the links between pages) and then the content of
pages. To evaluate the performance, the algorithm is compared with existing
algorithms. Experimental results show that RWP outperforms existing algorithms
to find relevant Web pages. RWP increases the search efficiency effectively and
enhances the application area of Web related research.
Keywords: Web mining, relevant pages, hyperlink analysis, content analysis.
1 Introduction
The World Wide Web is a rich source of information and continues to expand in
size and complexity. How to efficiently and effectively retrieve required Web
pages on the Web is becoming a challenge day by day [1–3]. There are many
ways to find relevant pages. For example, as indicated in [4], Netscape uses Web
page content analysis, usage pattern information, as well as linkage analysis to
find relevant pages. Among the approaches of finding relevant pages, hyperlink
analysis has its own advantages. Primarily, the hyperlink is one of the most
obvious features of the Web and can be easily extracted by parsing the Web page
codes. Most importantly, hyperlinks encode a considerable amount of latent
human judgment in most cases [5, 6].
Keywords
Web mining, relevant pages, hyperlink analysis, content analysis.
Related Book
Other papers in this volume
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