Adaptive Temporal Query Modeling

Maria-Hendrike Peetz, Edgar Meij, Maarten de Rijke, Wouter Weerkamp

Abstract: We present an approach to query modeling that uses the temporal distribution of documents in an initially retrieved set of documents. Such distributions tend to exhibit bursts, especially in news-related document collections. We hypothesize that documents in those bursts are more likely to be relevant and update the query model with the most distinguishing terms in high-quality documents sampled from bursts. We evaluate the effectiveness of our models on a test collection of blog posts.

External IDs:dblp:conf/ecir/PeetzMRW12