Predicting query performance

We develop a method for predicting query performance by computing the relative entropy between a query language model and the corresponding collection language model. The resulting clarity score measures the coherence of the language usage in documents whose models are likely to generate the query. We suggest that clarity scores measure the ambiguity of a query with respect to a collection of documents and show that they correlate positively with average precision in a variety of TREC test sets. Thus, the clarity score may be used to identify ine#ective queries, on average, without relevance information. We develop an algorithm for automatically setting the clarity score threshold between predicted…

• NS
  National Science Foundation