- James Allan, Jamie Callan, B. Croft, Lisa Ballesteros, J. Broglio, Jinxi Xu, Hongming Shu. 1997. Inquery at Trec-5 1 Ad-hoc Experiments. Abstract: The University of Massachusetts participated in ve tracks in TREC-5: Ad-hoc, Routing, Filtering , Chinese, and Spanish. Our results are generally positive, continuing to indicate that the techniques we have applied perform well in a variety of settings. Signiicant changes in our approaches include emphasis on identifying key concepts/terms in the query topics, expansion of the query using a variant of automatic feedback called \Local Context Analysis", and application of these techniques to a non-European language. The results show the broad applicability of Local Context Analysis, demonstrate successful identiication and use of key concepts, raise interesting questions about how key concepts aaect precision, support the belief that many IR techniques can be applied across languages, present an intriguing lack of tradeoo between recall and precision when ltering, and connrm once again several known results about query formulation and combination. Regrettably, three of our oocial submissions were marred by errors in the processing (an unde-tected syntax error in some queries, and an incomplete data set in an another case). The following discussion analyzes corrected runs as well as those (not particularly meaningful) submitted runs. Our experiments were conducted with version 3.1 of the INQUERY information retrieval system. INQUERY is based on the Bayesian inference network retrieval model. It is described elsewhere 5, 4, 12, 11], so this paper focuses on relevant diierences to the previously published algorithms. The emphasis in this year's Ad-Hoc experiments was on how to create very eeective queries from short natural language topics. In particular, how to create several rather diierent queries from the Description eld of the topic. The underlying assumption, based on past experience, was that a combination of several \pretty good" queries would be more eeective (or, at least easier to create) than one \excellent" query. Three techniques were explored. The rst, which we call basic query processing in this paper, is an extension of the query processing techniques we used in previous TREC evaluations. The second, which we call core query processing, attempted to identify and emphasize the most critical query terms. The third, local context analysis, is a new approach to query expansion 14]. Each technique is discussed in more detail in the subsections that follow. Two Ad-Hoc runs were submitted. Each query in INQ301 was a combination of three queries created from the Description (<desc>) elds of topics 251-300. Each query in INQ302 was a
