Sains Ma1aysiana 25(1):161-175 (1996)                                                                             Sains Matematik/

                                                                                                                                       Mathematical Sciences

Multi-stage Imaging Retrieval: A Relevance Feedback

Retrieval with Nearest Neighbour Clusters

Tengku Mohd. T. Sembok

Jabatan Sains Komputer

Universiti Kebangsaan Malaysia

43600 UKM Bangi Selangor D.E. Malaysia

ABSTRACT

Imaging Retrieval is a retrieval strategy which is based on modal logic where documents are viewed as possible worlds which are related through an accessibility relation established using their similarity/dissimilarity coefficients. With these accessibility relation documents are grouped into clusters based on a nearest neighbour concept. The work reported in this paper sets out to implement and evaluate the imaging retrieval as a relevance feedback retrieval with nearest neighbour clusters. The retrieval is implemented in two variations: a one-stage and a multi-stage retrieval. The results obtained from the experiments are enough to show the viability and validity of this strategy and to support it as something worth looking into further.

ABSTRAK

Capaian Imejan ialah satu strategi capaian yang berasaskan mantik yang menganggap dukumen sebagai dunia mungkin yang berkaitan. Kaitan antara dokumen ialah hubungan capaian yang dilahirkan dengan menggunakan koefisien persamaan. Dengan hubungan capaian ini dokumen boleh dikumpulkan dalam kelompok berdasarkan konsep jiran terdekat. Kerja yang dilaporkan dalam kertas ini bertujuan untuk melaksanakan dan menilai capaian imejan sebagai capaian kerelevanan bermaklum balas dengan kelompok jiran terdekat. Capaian tersebut dilaksanakan dalam dua bentuk: capaian satu tahap dan multi tahap. Hasil yang diperolehi dari eksperimen adalah mencukupi untuk menunjukkan keupayaan dan kesahan strategi ini dan memberi sokongan sebagai sesuatu yang patut dikaji dengan lebih mendalam.

RUJUKAN/REFERENCES

Croft, W. B.1978. Organizing and Searching Large Files of document Descriptions. Ph.D. Thesis, Churchill College, University of Cambridge.          

Fox, E. A.1983. Characterization of two New Experimental Collections in Computer and Information Science Containing Textual and Bibliographic Concepts. Technical Report 83-561, Department of Computer Science, Cornell University.

Harper D. J.1980. Relevance Feedback in Document Retrieval Systems: An Evaluation of Probabilistic Strategies. Ph.D Thesis, Jesus, College, Cambridge University.

Harper, W. L., Stalnaker, R., Pearce, C. (eds.). 1981. Ifs, Reidel. Salton, G.,Buckley, C. 1988. Parallel Text Search Methods. Communication of the ACM, Vol. 31, pp. 202-215.   

Sembok, T.M.T, & Van Rijsbergen, C. J. 1989. SILOL; A simple Logical-linguistic Document Retrieval System. Information Processing & Management, Vol.26, No.1, Pergamon Press, pp 111-134.  

Sembok, T. M. T., van Rijsbergen, C. J. 1993. IMAGING; A Relevance Feedback Retrieval with Nearest Neighbour Clusters, presented at the 15th BCS Research Colloquium in IR, University of Strathc1yde, Glasgow.

Smeaton, Alan. 1988. Using Parsing of Natural Language as part of Document Retrieval. Ph.D. Thesis, Department of Computer Science, University College Dublin, Ireland.

van Rijsbergen, C. J. 1979. Information Retrieval, 2nd edition. Butterworths.

van Rijsbergen C. J. 1989. Towards and Information Logic. Research Report CSC/89/R8, Dept. of Computing Science, University of Glasgow.