Improved Fuzzy and Neural Network Algorithms tor Word Frequency Prediction in Document Filtering1

Journal of Advanced Computational Intelligence and Intelligent Informatics

Volumn 2, Issue 3, 1998, Pages 88-95

  Baranyi, Peter ^a   Koczy, Laszlo T ^a   Gedeon, Tamas D ^b  

^a BUDAPEST UNIVERSITY OF TECHNOLOGY AND ECONOMICS   (Hungary)

^b UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

Fuzzy logic; Information retrieval; Neural network; Parameter set reduction

Indexed keywords

COMPUTER CIRCUITS; DATA MINING; FUZZY INFERENCE; FUZZY NEURAL NETWORKS; INFORMATION RETRIEVAL; LINGUISTICS; SEARCH ENGINES;

% REDUCTIONS; DOCUMENT COLLECTION; FREQUENCY PREDICTION; FUZZY NETWORKS; FUZZY-LOGIC; NEURAL NETWORKS ALGORITHMS; NEURAL-NETWORKS; PARAMETER SET; PARAMETER SET REDUCTION; WORD FREQUENCIES;

INFORMATION RETRIEVAL SYSTEMS;

EID: 0002824372     PISSN: 13430130     EISSN: 18838014     Source Type: Journal    
DOI: 10.20965/jaciii.1998.p0088     Document Type: Article

References (17)

1. 1 Proc. of NOLTA'93 Int. Conf. Non-Linear Theory and Applications, 771-777, (1993>
2. Busios, R.A,T Gedeon, T.D., "Learning Synonyms and Related Concepts in Document Collect ions,* in Alspcctor, JT, Goodmanf, R. And Brown, T.X. Applications of Neural Networks to Telecommunications 2, [jiWTcncc Erlbaum, 2112-2(19, (1995),
3. Koczy, LT\, Gedeon, T.D., "Information retrieval by fuzzy relations and hierarchical cooccurrence," IETR 97/3 Dcpt. Information Lnyineering School of Comp. Science and lngr Univ. of NSW. TR 97/3 Sydney* (1993).
4. Mr Mizumoto, "Fuzzy contols by product-sum-gravity method, Advancement ot ruzzy l neory and systems in L nina anu Japan, cus. Liu and Mizumolo, International Academic Publishers. cL1-cl.4, i 1990)
5. Gedeon, T,D, and Mital, V., "Information Retrieval Using a Neural Network Integrated with Hypenex t roc. ot n . on eura c - works. 1819-1824, (1991),
6. ft) Rose D, and Bclew R.h "A Connectionist and symbolic Hybrid for improving Research, Int. J. Man ae me b u ics v. „ [
7. Blair D.C, "Language and Representation in Information Retrieval* Amsterdam, Elsevier, <199l).
8. Blair, D.C and Marron, M,E., "An Evaluation of Retrieval Effectiveness for a rull- ext Documeni Ketneva System, ~H9-299, (1985).
9. Puice, CD,, "Constructing Lilcraturc Abstracts by Computer; Techniques and Prospects, Info. Proc, and Management, 26-1, - Bo, (199(1),
10. Fischer G. and Stevens C, "Information access m complex, poorly structured information spaces, roc o on erencc, {).
11. Foltz, P.W. and Dumais, S/T, "Personalized intormation delivery: an analysis of informal ion filtering methods/' CACM, 35-12, 51-btK (1992),
12. Goldberg, Dr. Nichols, D,, Oki, B.M. and Terry, D,, "Using collaborative tillering to weave an information tapestry," CACM, 35-12, ol-7M, (1992).
13. Brookes, C, "grapcVtNE: Concepts and Applications,'* Office Express Pty, lJd.(l99l),
14. Salton, G- "The SMART Retrieval System — Experiment in Automatic DiK-'ument Processing/' Englewood Cliffs, Prentice-Hall, (1971 J.
15. J J1)
16. Turtle, il, "Text Retrieval in the Legal World," Artificial lindligencc and the l-aw, 3, 97-142, (1995)
17. Sallon, G., ''Automatic Texi Processing; The Transformation, Analysis, and Retrieval of Information by Computer, Addison Wesley, (1989).