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TítuloRelevance based language models : new estimations and applications

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Academic year: 2020

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Table 3.1: Collections and topics for training and test used in the document retrieval evaluation
Table 4.1: Values for Mean Average Precision (MAP) on the test topics. Sta- Sta-tistical significant improvements (Wilcoxon p < 0.1, and Wilcoxon p < 0.05 underlined) with respect to LM, RM3, Resampling, and CBRM3 are  super-scripted with l, r, s, an
Figure 5.1: RM3 behaviour in terms of Average Precision for different queries from the training query set of the AP-8889 collection with t = 100 and λ = 0.8 and µ = 1000
Figure 5.2: Mixture of Gaussians fit to relevant and non-relevant data ob- ob-tained processing the scores of TREC query 154 over the AP88-89 collection produced with the LM retrieval function with Dirichlet smoothing (µ = 1000)
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