document: Search shortcuts : driving users towards their goals Giving suggestions to users of Web-based services is a common practice aimed at enhancing their navigation experience . Major Web Search Engines usually provide `` Suggestions '' under the form of queries that are , to some extent , related to the current query typed by the user , and the knowledge learned from the past usage of the system . In this work we introduce `` Search Shortcuts '' as `` Successful '' queries allowed , in the past , users to satisfy their information needs . Differently from conventional suggestion techniques , our search shortcuts allows to evaluate effectiveness by exploiting a simple train-and-test approach . We have applied several Collaborative Filtering algorithms to this problem , evaluating them on a real query log data . We generate the shortcuts from all user sessions belonging to the testing set , and measure the quality of the shortcuts suggested by considering the similarity between them and the navigational user behavior .
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