Term importance, Boolean conjunct training, negative terms, and foreign language retrieval: probabilistic algorithms at TREC-5.

The Berkeley experiments for TREC-5 extend those of T RECE-4 in numerous way, and experiments with the idea of term importance in three ways - training on Boolean conjuncts of the most important terms, filtering with the mostImportant terms, and logistic regression on presence or absence of those terms.

Abstract

The Berkeley experiments for TREC-5 extend those of TREC-4 in numerous ways. For routing retrieval we experimented with the idea of term importance in three ways -- training on Boolean conjuncts of the most important terms, filtering with the most important terms, and, finally, logistic regression on presence or absence of those terms. For ad-hoc retrieval we retained the manual reformulations of the topics and experimented with negative query terms. The ad-hoc retrieval formula originally devised for TREC-2 has proven to be robust, and was used for the TREC-5 ad-hoc retrieval and for our Chinese and Spanish retrieval. Chinese retrieval was accomplished through development of a segmentation algorithm which was used to augment a Chinese dictionary. The manual query run BrklyCH2 achieved a spectacular 97.48 percent recall over the 19 queries evaluated before the conference. 1. Introduction From the beginning of the TREC conference series, the UC Berkeley Text Retrieval Research Group ha...