Comparing Weighting Models for Monolingual Information Retrieval
Motivated by the hypothesis that the retrieval performance of a weighting model is independent of the language in which queries and collection are expressed, we compared the retrieval performance of three weighting models, i.e., Okapi, statistical language modeling (SLM), and deviation from randomness (DFR), on three monolingual test collections, i.e., French, Italian, and Spanish. The DFR model was found to consistently achieve better results than both Okapi and SLM, whose performance was comparable. We also evaluated whether the use of retrieval feedback improved retrieval performance; retrieval feedback was beneficial for DFR and Okapi and detrimental for SLM. Besides relative performance, DFR with retrieval feedback achieved excellent absolute results: best run for Italian and Spanish, third run for French.
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