QueryDifficulty

In

G. Amati, C. Carpineto and G. Romano. Query Difficulty, Robustness, and Selective Application of Query Expansion. In Advances in Information Retrieval, 26th European Conference on IR Research, ECIR 2004. Pages 127-137. Sunderland, UK. April, 2004.

Amati et. al. proposed the query difficulty, which is applied for the Query Performance Prediction.

The query difficulty measures the divergence of a term's distribution in the top-ranked documents from its distribution in the whole collection. The notion is also related with the DFRTermWeightingModels for QueryExpansion.

Terrier employs the Bo1, Bo2 and KL DFRTermWeightingModels.