Abraham Bookstein
- 1.Lancaster, F.W. Information Retrieval Systems: Characteristics, Testing aqd (2nd Ed). New York: Wiley- Interscience. 1979.Google Scholar
- 2.Salton, G. and McGill, H.J. Introduction }Lq ~Qdern Informat~0n Retrieval. New York: HcGraw Hill. 1983. Google ScholarDigital Library
- 3.Cooper, W.S. "Exploiting the ~,'aximum Entropy Principle to Increase Retrieval Effectiveness." Journal o~ ~he American Society for Information Science. 1983; 34 (I): 31-39.Google Scholar
- 4.Roochlo, J.J. Relevance Feedback in Information Retrieval. In: Salton, G. (ed.) The SMART Retrivail Svstem_L Experiments in Automatic Document Processing. Englewood Cliffs, N.J.: Prentice-Hall. 1971.Google Scholar
- 5.Bookstein, A. and Swanson D. "A Decision Theoretic Foundation for Indexing." Journal of The American Society for Information Science. 1975; 26: 45-50.Google Scholar
- 6.Robertson, S.E. and Sparck-Jones, K. "RelevanceWeighting of Search Terms." Journal 9.~ the American Society ~'or Information Science. 1976; 27: 129- 146.Google Scholar
- 7.Radeck$, T. ,Fuzzy ~et Theoretical Approach to Document Retrieval." ~.q~LgJ~Lq~ Processing and. {mna~ement. 1979; 15: 247-59.Google Scholar
- 8.Bookstein, A. "Fuzzy Requests." Journal ~Z~ the American Society ~OZ Information Science. 1980; 31 (3): 240--47.Google Scholar
- 9.Bookstein, A. "Outline of a General Probabilistic Retrieval Hodel." Journal ~ ~geumentation. 1983; 39 (2): 63-72.Google Scholar
- 10.Salton, G., Fox, E.A. and Wu, H. "Extended Boolean Information Retrieval." Communications ~_~ the ACi!. 1983; 26 (12): 1022-1036. Google ScholarDigital Library
- 11.Robertson, S.E. "The Probability Ranking Principle in IR." Journal ~_~ Documentation. 1977; 33: 294-304.Google Scholar
- 12.Tague, J. and Nelson, M. "Simulation of Bibliographic Databases Using Hyperterms." In: Saiton, G. and Schneider, H-J (eds). Research and Development in Information Retrieval. Berlin: Springer-Verlag; 1983. Google ScholarDigital Library
Recommendations
On a combination of probabilistic and boolean ir models for WWW document retrieval
Even though a Boolean query can express the information need precisely enough to select relevant documents, it is not easy to construct an appropriate Boolean query that covers all relevant documents. To utilize a Boolean query effectively, a mechanism ...
Properties of the probabilistic implications and S-implications
Recently, Grzegorzewski (2011) introduced two new families of fuzzy implication functions called probabilistic implications and probabilistic S-implications. They are based on conditional copulas and make a bridge between probability theory and fuzzy ...
Representing boolean structure within a probabilistic framework
RIAO '85: Recherche d'Informations Assistée par OrdinateurTheorists interested in Information Retrieval have long argued the relative advantages of Probabilistic versus Boolean/Fuzzy-Set retrieval. In this paper it is suggested that the most characteristic properties of each can be realized in the other, and, ...
Comments