University of Padua at TREC 2009: Relevance Feedback Track

摘要

In the Relevance Feedback (RF) task the user is directly involved in the search process: given an initial set of results, he specifies if they are relevant or not to the achievement of his information goal. In the TREC 2009 RF track the first five documents retrieved by the baseline systems were judged by the assessors and then used as evidence for the RF algorithms to be tested. The specific algorithm we tested is mainly based on a geometric framework which allows the latent semantic associations of terms in the feedback documents to be modeled as a vector subspace; the documents of the collection represented as vectors of TFIDF weights were re-ranked according to their distance from the subspace. The adopted geometric framework was used in past works as a basis for Implicit Relevance Feedback (IRF) and Pseudo Relevance Feedback (PRF) algorithms; the participation to the RF track allows us to make some preliminary investigations on the effectiveness of the adopted framework when it is exploited to support explicit RF on much larger test collections, thus complementing the work carried out for the other RF strategies.