document: Generalized link suggestions via web site clustering Proactive link suggestion leads to improved user experience by allowing users to reach relevant information with fewer clicks , fewer pages to read , or simply faster because the right pages are prefetched just in time . In this paper we tackle two new scenarios for link suggestion , which were not covered in prior work owing to scarcity of historical browsing data . In the web search scenario , we propose a method for generating quick links - additional entry points into Web sites , which are shown for top search results for navigational queries - for tail sites , for which little browsing statistics is available . Beyond Web search , we also propose a method for link suggestion in general web browsing , effectively anticipating the next link to be followed by the user . Our approach performs clustering of Web sites in order to aggregate information across multiple sites , and enables relevant link suggestion for virtually any site , including tail sites and brand new sites for which little historical data is available . Empirical evaluation confirms the validity of our method using editorially labeled data as well as real-life search and browsing data from a major US search engine .
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