TREC-3 Ad-Hoc, Routing Retrieval and Thresholding Experiments using PIRCS.
Published 1 January 1994
K. L. Kwok, Laszlo Grunfeld, David Lewis
Citations39
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TL;DR
The PIRCS retrieval system has been upgraded in TREC-3 to handle the full English collections of 2 GB in an efficient manner and recurrent spreading of activation in the network is used to implement query learning and expansion based on the best-ranked subdocuments of an initial retrieval.
Abstract
The PIRCS retrieval system has been upgraded in TREC-3 to handle the full English collections of 2 GB in an efficient manner. For ad-hoc retrieval, we use recurrent spreading of activation in our network to implement query learning and expansion based on the best-ranked subdocuments of an initial retrieval. We also augment our standard retrieval algorithm with a soft-Boolean component. For routing, we use learning from signal-rich short documents or subdocument segments. For the optional thresholding experiment, we tried two approaches to transforming retrieval status values (RSV's) so that they could be used to partition documents into retrieved and nonretrieved sets. The first method normalizes RSV's using a query self-retrieval score. The second, which requires training data, uses logistic regression to convert RSV's into estimates of probability of relevance. Overall, our results are highly competitive with those of other participants. 1. INTRODUCTION PIRCS is an experimental info...
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Computer Science
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