USC/ISI at TREC 2011: Microblog Track

Donald Metzler, Congxing Cai
2011 Text Retrieval Conference  
This paper describes the search system we developed for the inaugural TREC 2011 Microblog Track. Our system makes use of best-practice ranking techniques, including term, phrase, and proximity-based text matching via the Markov random field model, pseudo-relevance feedback using Latent Concept Expansion, and a feature-based ranking model that uses a simple, but effective learningto-rank model. We adapted each of these approaches to the specifics of the microblog search task, giving rise to a
more » ... hly effective end-to-end search system. The official results from the TREC evaluation suggest that pseudorelevance feedback and learning-to-rank yield significant improvements in precision at early rank under different evaluation scenarios.
dblp:conf/trec/MetzlerC11 fatcat:t2dgxf366ffthdlemuh236wo2a