General Terms

Users who need several queries before finding what they need can benefit from an automatic search assistant that provides feedback on their query modification strategies. We present a method to learn from a search log which types of query modifications have and have not been effective in the past. The method analyses query modifications along two dimen-sions: a traditional term-based dimension and a semantic di-mension, for which queries are enriches with linked data en-tities. Applying the method to the search logs of two search engines, we identify six opportunities for a query modifi-cation assistant to improve search: modification strategies that are commonly used, but that often do not lead to sat-isfactory results. 1