- James Allan, Jamie Callan, M. Sanderson, Jinxi Xu, S. Wegmann. 2004. Inquery and Trec-7 (draft|workshop Notebook Version). Abstract: ipated in only four of the tracks that were part of the TREC-7 workshop. We worked on ad-hoc retrieval, ltering, VLC, and the SDR track. This report covers the work done on each track successively. We start with a discussion of IR tools that were broadly applied in our work. Although UMass used a wide range of tools, from Unix shell scripts, to PC spreadsheets, three major tools were applied across almost all tracks: the Inquery search engine, the InRoute ltering engine, and a a query expansion technique known as LCA. This section provides a brief overview of each of those so that the discussion does not have to repeated for each track. 1.1 Inquery All tracks other than the ltering track used Inqueryy6] as the search engine, sometimes for training, and always for generating the nal ranked lists for the test. We used Inquery V3.2, an in-house development version of the Inquery system made available by the CIIR (V3.1). The diierences between the two are not consequential for this study. The current belief function used by Inquery to calculate the belief in term t within document d is: w t;d = 0:4 + 0:6 tf t;d tf t;d + 0:5 + 1:5 length(d) avg len log N+0:5 nt log N + 1 where n t is the number of documents containing term t, N is the number of documents in the collection, \avg len" is the average length (in words) of documents in the collection, length(d) is the length (in words) of document d, and tf t;d is the number of times term t occurs in document d.
