Browsing by Subject "Hypertext systems"
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Item Open Access Incorporating the surfing behavior of web users into PageRank(ACM, 2013-10-11) Ashyralyyev, Shatlyk; Cambazoğlu, B. B.; Aykanat, CevdetIn large-scale commercial web search engines, estimating the importance of a web page is a crucial ingredient in ranking web search results. So far, to assess the importance of web pages, two different types of feedback have been taken into account, independent of each other: the feedback obtained from the hyperlink structure among the web pages (e.g., PageRank) or the web browsing patterns of users (e.g., BrowseRank). Unfortunately, both types of feedback have certain drawbacks. While the former lacks the user preferences and is vulnerable to malicious intent, the latter suffers from sparsity and hence low web coverage. In this work, we combine these two types of feedback under a hybrid page ranking model in order to alleviate the above-mentioned drawbacks. Our empirical results indicate that the proposed model leads to better estimation of page importance according to an evaluation metric that relies on user click feedback obtained from web search query logs. We conduct all of our experiments in a realistic setting, using a very large scale web page collection (around 6.5 billion web pages) and web browsing data (around two billion web page visits). Copyright is held by the owner/author(s).Item Open Access Towards a quality service layer for Web 2.0(Springer, 2011-12) Schaal, M.; Davenport, David; Çevik, Ali HamdiDespite the help of search engines and Web directories, identifying high quality content becomes increasingly difficult as the Internet gets ever more crowded with information. Prior approaches for filtering and searching content with respect to user-specific preferences do exist: Recommendation engines employ collaborative filtering to support subjective selection, (semi-)automatic page ranking algorithms utilize the hypertext link structure of the World Wide Web to assess page importance, and trust-based systems employ social network analysis to determine the most suitable Web pages. The use of implicit and explicit user feedback, however, is often either ignored or its exploitation is limited to isolated Web sites. We thus propose a quality overlay framework that enables the collection and processing of user-feedback, and the subsequent presentation of quality-enabled content for any Web-site. We present the quality overlay framework, propose an architecture for its realization, and validate our approach by scenarios and a detailed design with sample implementation. © 2011 Springer-Verlag.