No abstract

Social bookmarking services have become recently popular in the Web. Along with the rapid increase in the amount of social bookmarks, future applications could leverage this data for enhancing search in the Web. This paper investigates the possibility and potential benefits of a hybrid page ranking approach that would combine the ranking criteria of PageRank with the one based on social bookmarks in order to improve the search in the Web. We demonstrate and discuss the results of analytical study made in order to compare both popularity estimates. In addition, we propose a simple hybrid search method that combines both ranking metrics and we show some preliminary experiments using this approach. We hope that this study will shed new light on the character of data in social bookmarking systems and foster development of new, effective search applications for the Web.

We describe a new concept for improving Web search performance and/or increasing the information credibility of search results using Web1.0 and Web2.0 content in a complementary manner. Conventional Web search engines still suffer from a low precision/recall ratio, especially for searching multimedia content (images, videos etc.). The quality control of Web search is

Social bookmarking is an emerging type of a Web service for reusing, sharing, and discovering resources. By bookmarking, users preserve access points to encountered documents for their future access. On the other hand, the social aspect of bookmarking results from the visibility of bookmarks to other users helping them to discover new, potentially interesting resources. In addition, social bookmarking systems allow for better estimation of the popularity and relevance of documents. In this chapter, we provide an overview of major aspects involved with social bookmarking and investigate their potential for enhancing Web search and for building novel applications. We make a comparative analysis of two popularity measures of Web pages, PageRank and SBRank, where SBRank is defined as an aggregate number of bookmarks that a given page accumulates in a selected social bookmarking system. The results of this analysis reveal the advantages of SBRank when compared to PageRank measure and provide the foundations for utilizing social bookmarking information in order to enhance and improve search in the Web. In the second part of the chapter, we describe an application that combines SBRank and PageRank measures in order to rerank results delivered by Web search engines and that offers several complimentary functions for realizing more effective search.