The ongoing explosion of web information calls for more intelligent and
personalized methods towards better search result quality for advanced queries.
Query logs and click streams obtained from web browsers or search engines can
contribute to better quality by exploiting the collaborative recommendations
that are implicitly
embedded in this information. The method presented in this work incorporates
the notion of query nodes into the PageRank model and integrates the implicit
relevance feedback given by click streams into the automated process of
The enhanced PageRank scores, coined QRank scores, can be computed oine; at
query-time they are combined with query-specific relevance measures with
virtually no overhead. In our experiments significant improvements in the
precision of search results were observed, which demonstrate the eectiveness
of our model.