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Query logs record the actual usage of search systems and
their analysis has proven critical to improving search engine
functionality. Yet, despite the deluge of information, query
log analysis often suffers from the sparsity of the query space.
Based on the observation that most queries pivot around a
single entity that represents the main focus of the user’s
need, we propose a new model for query log data called the
entity-aware click graph. In this representation, we decom-
pose queries into entities and modifiers, and measure their
association with clicked pages. We demonstrate the benefits
of this approach on the crucial task of understanding which
websites fulfill similar user needs, showing that using this
representation we can achieve a higher precision than other
query log-based approaches.