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Journal of the American Society for Information Science
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Extracting macroscopic information from Web links
Journal of the American Society for Information Science and Technology
The structure of broad topics on the web
Proceedings of the 11th international conference on World Wide Web
Journal of the American Society for Information Science and Technology
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Journal of the American Society for Information Science and Technology
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IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Exploiting hyperlinks to study academic Web use
Social Science Computer Review
Combining link-based and content-based methods for web document classification
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Visualizing linguistic and cultural differences using Web co-link data: Research Articles
Journal of the American Society for Information Science and Technology
Hierarchical topic segmentation of websites
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Co-citations as citation endorsements and co-links as link endorsements
Journal of Information Science
Web hyperlink patterns and the financial variables of the global banking industry
Journal of Information Science
Journal of the American Society for Information Science and Technology
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A common task in both Webmetrics and Web information retrieval is to identify a set of Web pages or sites that are similar in content. In this paper we assess the extent to which links, colinks and couplings can be used to identify similar Web sites. As an experiment, a random sample of 500 pairs of domains from the UK academic Web were taken and human assessments of site similarity, based upon content type, were compared against ratings for the three concepts. The results show that using a combination of all three gives the highest probability of identifying similar sites, but surprisingly this was only a marginal improvement over using links alone. Another unexpected result was that high values for either colink counts or couplings were associated with only a small increased likelihood of similarity. The principal advantage of using couplings and colinks was found to be greater coverage in terms of a much larger number of pairs of sites being connected by these measures, instead of increased probability of similarity. In information retrieval terminology, this is improved recall rather than improved precision.