Improving Query Expansion for Information Retrieval Using Wikipedia
Lixin Gan, Huan Hong · International Journal of Database Theory and Application · 2015
Query expansion (QE) is one of the key technologies to improve retrieval efficiency.Many studies on query expansion with relationships from single local corpus suffer from two problems resulting in low retrieval performance: term relationships are limited and unlisted query terms have no expansion terms.To address these problems, relationships between terms captured from Wikipedia are superimposed to the basic Markov network that pre-built using single local corpus.A new larger Markov network is formed with more and richer relationship for each term.Evaluation is performed on three standard information retrieval corpuses including ADI, CISI and CACM.Experimental results show that the proposed technique of superimposed Markov network is effective to select more and confident candidatesfor query expansion and it outperforms other state-of-the-art QE methods.