Axiomatic Analysis and Optimization of Information Retrieval Models
ChengXiang Zhai, Hui Min Fang · 2013
The accuracy of a search engine is mostly determined by the optimality of the retrieval model used in the search engine. Develoing optimal retrieval models has always been a very important fundamental research problem in information retrieval because an improved general retrieval model would enable all search engines to be more useful, thus have immediate broad impact. Extensive research has been done on developing an optimal retrieval model since 1960s, leading to multiple effective retrieval models, including, e.g., Pivoted Normalization Vector Space model, BM25, Dirichlet Prior Query Likelihood, and PL2. However, these state of the art retrieval models were all developed at least a decade ago, suggesting that it has been difficult to further improve them. One reason why we could not easily improve these models is because we do not have a good understanding of their deficiencies and have mostly relied on empirical evaluation to assess the superiority of a retrieval model.