Re-ranking Method Based on Topic Word Pairs

摘要

How to improve the rankings of the relevant documents plays a key role in information retrieval. In this paper, a re-ranking approach based on topic words pair is proposed to improve precision while recall is preserved. The topic word pairs contain two correlated words, one of which is the original query word and the other come from the documents. The selection is based on Probabilistic Latent Semantic Indexing (PLSI). Then, the distribution of the word pairs is used to re-rank documents. Results show a 53.6% and 56.8% improvement compare to the initial retrieval without any re-ranking or query expansion on NTCIR-5 document collection for SLIR.