LinkSelector
Xiao Fang, Olivia R. Liu Sheng
Abstract
Xiao Fang, Olivia R. Liu Sheng
Abstract
As the size and complexity of Web sites expands dramatically, it has become increasingly challenging to design Web sites where Web surfers can easily find the information they seek. In this article, we address the design of the portal page of a Web site, which serves as the homepage of a Web site or a default Web portal. We define an important research problem---hyperlink selection: selecting from a large set of hyperlinks in a given Web site, a limited number of hyperlinks for inclusion in a portal page. The objective of hyperlink selection is to maximize the efficiency, effectiveness, and usage of a Web site's portal page. We propose a heuristic approach to hyperlink selection, LinkSelector, which is based on relationships among hyperlinks---structural relationships that can be extracted from an existing Web site and access relationships that can be discovered from a Web log. We compared the performance of LinkSelector with that of the current practice of hyperlink selection (i.e., manual hyperlink selection by domain experts), using data obtained from the University of Arizona Web site. Results showed that LinkSelector outperformed the current manual selection method.
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As the size and complexity of Web sites expands dramatically, it has become increasingly challenging to design Web sites where Web surfers can easily find the information they seek. In this article, we address the design of the portal page of a Web site, which serves as the homepage of a Web site or a default Web portal. We define an important research problem---hyperlink selection: selecting from a large set of hyperlinks in a given Web site, a limited number of hyperlinks for inclusion in a portal page. The objective of hyperlink selection is to maximize the efficiency, effectiveness, and usage of a Web site's portal page. We propose a heuristic approach to hyperlink selection, LinkSelector, which is based on relationships among hyperlinks---structural relationships that can be extracted from an existing Web site and access relationships that can be discovered from a Web log. We compared the performance of LinkSelector with that of the current practice of hyperlink selection (i.e., manual hyperlink selection by domain experts), using data obtained from the University of Arizona Web site. Results showed that LinkSelector outperformed the current manual selection method.
Key concepts: Hyperlink, Computer science, World Wide Web, Web page, Web modeling, Data Web, Selection (genetic algorithm), Information retrieval