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Treffer: TREC-5 Ad Hoc retrieval using K nearest-neighbors Re-scoring

Title:
TREC-5 Ad Hoc retrieval using K nearest-neighbors Re-scoring
Source:
TREC-5 Text REtrieval ConferenceNIST special publication. (500238):415-425
Publisher Information:
Gaithersburg, MD: National Institute of Standards and Technology, 1997.
Publication Year:
1997
Physical Description:
print, 5 ref
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
IBM T. J. Watson Research Center, POB 718, Yorktown Heights, NY 10598, United States
ISSN:
1048-776X
Rights:
Copyright 1998 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Sciences of information and communication. Documentation

FRANCIS
Accession Number:
edscal.2237094
Database:
PASCAL Archive

Weitere Informationen

AA. focus on improving on baseline results obtained from another search engine by means of automatic query expansion. They call the specific formula used for query expansion Knn re-scoring, where Knn stands for K nearest-neighbors. The first-pass ranking is done using Okapi system's basic scoring formula. The documents are theen rescored using the same formula with the top-ranked K documents as queries, weighted according to their first-pass scores. The formula is motivated by viewing the rescoring process as a Markov process. This approach improves the precision outside the topK retrieved documents. They have implemented a query expansion scheme using all the words and some of the bigrams in the topK documents.