A probabilistic inference model for information retrieval

Information Systems

Volumn 16, Issue 3, 1991, Pages 301-321

  Wong, S K M ^a   Yao, Y Y ^a  

^a UNIVERSITY OF REGINA   (Canada)

Author keywords

indexing; inference; Information retrieval; probabilistic model; query formulation; relevance feedback; vector space model

Indexed keywords

EID: 0043154185     PISSN: 03064379     EISSN: None     Source Type: Journal    
DOI: 10.1016/0306-4379(91)90003-R     Document Type: Article

References (49)

1. Term weighting approaches in automatic text retrieval
2. Recent trends in automatic information retrieval
3. Query formulation in linear retrieval models
4. Improving retrieval performance by relevance feedback
5. Linear structure in information retrieval
6. Relevance feedback in information retrieval
7. Relevance feedback and the optimization of retrieval effectiveness
8. Relevance
9. Relevance: a review of and a framework for the thinking on the notion of information science
10. Situational relevance
11. A definition of relevance for information retrieval
12. OPENING THE BLACK BOX OF ‘RELEVANCE’
13. Subjective probability and information retrieval: a review of the psychological literature
14. Relevance weighting of search terms
15. Precision weighting—an effective automatic indexing method
16. The maximum entropy principle and its application to the design of probabilistic retrieval systems
17. A combination of expert opinion approach to probabilistic information retrieval, part 1: the conceptual model
18. A combination of expert opinion approach to probabilistic information retrieval, part 2: mathematical treatment of CEO model 3
19. Probability of relevance: a unification of two competing models for document retrieval
20. A non-classical logic for information retrieval
21. A new theoretical framework for information retrieval
22. An information retrieval model based on modal logic
23. Retrieving documents by plausible interference: a preliminary study
24. An outline of a general model for information retrieval systems
25. Inference network for document retrieval
26. Retrieving documents by plausible inference: an experimental study
27. A retrieval model for incorporating hypertert links
28. On modeling of information retrieval concepts in vector spaces
29. Generalized vector space model in information retrieval
30. A generalized term dependence model in information retrieval
31. Probabilities of conditionals and conditional probabilities
32. Approximating discrete probability distributions with dependence trees
33. A STATISTICAL INTERPRETATION OF TERM SPECIFICITY AND ITS APPLICATION IN RETRIEVAL
34. Concepts of the cover coefficient-based clustering methodology
35. A machine learning approach to information retrieval
36. Information retrieval: a sequential learning process