For many hard queries, users spend a lot of time refining their queries to find relevant documents. Many methods help by suggesting refinements, but it is hard for users to choose the best refinement, as the best refinements are often quite obscure. This paper presents Qasp, an approach that overcomes the limitations of other refinement approaches by using query aspects to find different refinements of ambiguous queries. Qasp clusters the refinements so that descriptive refinements occur together with more obscure and potentially better performing refinements, thereby explaining the effect of refinements to the user. Experiments are presented that show Qasp significantly increases the precision of hard queries. The experiments also show that Qasp's clustering method does find meaningful groups of refinements that help users choose good refinements, which would otherwise be overlooked.

@INPROCEEDINGS{UQA07,
    AUTHOR =    {Daniel Crabtree and Peter Andreae and Xiaoying Gao},
    TITLE =     {Understanding Query Aspects with applications 
                 to Interactive Query Expansion},
    BOOKTITLE = {The 2007 IEEE/WIC/ACM International Conference 
                 on Web Intelligence (WI'07)},
    YEAR =      {2007},
    PAGES =     {691--695}
}