Guided Local Search for query reformulation using weight propagation

Issam Moghrabi

International Journal of Applied Mathematics and Computer Science (2006)

  • Volume: 16, Issue: 4, page 537-549
  • ISSN: 1641-876X

Abstract

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A new technique for query reformulation that assesses the relevance of retrieved documents using weight propagation is proposed. The technique uses a Guided Local Search (GLS) in conjunction with the latent semantic indexing model (to semantically cluster documents together) and Lexical Matching (LM). The GLS algorithm is used to construct a minimum spanning tree that is later employed in the reformulation process. The computations done for Singular Value Decomposition (SVD), LM and the minimum spanning tree are necessary overheads that occur only initially and all subsequent work is based on them. Our experimental results reveal the effectiveness of the new technique.

How to cite

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Moghrabi, Issam. "Guided Local Search for query reformulation using weight propagation." International Journal of Applied Mathematics and Computer Science 16.4 (2006): 537-549. <http://eudml.org/doc/207812>.

@article{Moghrabi2006,
abstract = {A new technique for query reformulation that assesses the relevance of retrieved documents using weight propagation is proposed. The technique uses a Guided Local Search (GLS) in conjunction with the latent semantic indexing model (to semantically cluster documents together) and Lexical Matching (LM). The GLS algorithm is used to construct a minimum spanning tree that is later employed in the reformulation process. The computations done for Singular Value Decomposition (SVD), LM and the minimum spanning tree are necessary overheads that occur only initially and all subsequent work is based on them. Our experimental results reveal the effectiveness of the new technique.},
author = {Moghrabi, Issam},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {relevance feedback; latent semantic; clustering; query reformulation; lexical matching},
language = {eng},
number = {4},
pages = {537-549},
title = {Guided Local Search for query reformulation using weight propagation},
url = {http://eudml.org/doc/207812},
volume = {16},
year = {2006},
}

TY - JOUR
AU - Moghrabi, Issam
TI - Guided Local Search for query reformulation using weight propagation
JO - International Journal of Applied Mathematics and Computer Science
PY - 2006
VL - 16
IS - 4
SP - 537
EP - 549
AB - A new technique for query reformulation that assesses the relevance of retrieved documents using weight propagation is proposed. The technique uses a Guided Local Search (GLS) in conjunction with the latent semantic indexing model (to semantically cluster documents together) and Lexical Matching (LM). The GLS algorithm is used to construct a minimum spanning tree that is later employed in the reformulation process. The computations done for Singular Value Decomposition (SVD), LM and the minimum spanning tree are necessary overheads that occur only initially and all subsequent work is based on them. Our experimental results reveal the effectiveness of the new technique.
LA - eng
KW - relevance feedback; latent semantic; clustering; query reformulation; lexical matching
UR - http://eudml.org/doc/207812
ER -

References

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  1. Baeza-Yates R. and Ribeiro-Neto B. (1999): Modern Information Retrieval. - New York: Prentice Hall. 
  2. Daniels J. and Rissland, E. (1995): EXPRESS: A case based approach to intelligent information retrieval. - Proc. SIGIR'95 Conf., Seattle, WA, USA 1995, pp. 31-43. 
  3. Dunlop M.D. (1997): The effect of accessing non-matching documents on relevance feedback. - ACM Trans. Inf. Syst., Vol. 15, No. 2, pp. 137-153. 
  4. Epp S.S. (1990): Discrete Mathematics with Applications. - London: Wadsworth Publishing Company. Zbl0714.00001
  5. Letsche T.A. and Berry M.W. (1997): Large-scale information retrieval with latent semantic indexing. - Inf. Sci., Vol. 9, No. 2, pp. 111-121. 
  6. Lopez-Pujalte C., Guerrero-Bote V.P., de Moya-Anegon F. (2002): A test of genetic algorithms in relevance feedback. - Inf. Process. Manag., Vol. 38, No. 7, pp. 793-805. Zbl1027.68148
  7. Ruthven I., Tombros A. and Jose J. (2001): A study on the use of summaries and summary-based query expansion for a question-answering task. - Proc. 23rd BCS European Annual Colloquium on s Information Retrieval Research, Berlin, Germany, pp. 48-54. 
  8. Ruthven I., White R. and Jose J.M. (2001): Web document summarization: A task-oriented evaluation. -Proc. Int. Workshop s Digital Libraries, Proc. 12-th Int. Conf. s Database and Expert Systems Applications, (DEXA 2001), Munich, Germany, pp. 52-61. 
  9. Van R. (1979): Information Retrieval, 2nd Ed., London: McGraw Hill. 
  10. Voudouris C. and Tsang E. (1994): Tunneling algorithm for partial CSPs and combinatorial optimization problems. - Tech. Rep. No. CSM-213, Dept. of Computer Science, University of Essex, Colchester, UK. 
  11. Voudouris C. (1997): Guided Local Search for Combinatorial Optimisation Problems. - Ph.D. thesis, Dept. Computer Science, University of Essex, Colchester, UK. Zbl0882.90102

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