Enhancing the Power of the Internet pp 47-62 | Cite as
Intelligent Web Searching Using Hierarchical Query Descriptions
Chapter
Abstract
We describe a document retrieval language which enables a user to better represent their requirements with respect to the desired documents to be retrieved. This language allows for a specification of the interrelationship between the desired attributes using linguistic quantifiers. This framework also supports a hierarchical formulation of queries. These features allow for an increased expressiveness in the queries that be handled by a retrieval system.
Keywords
document retrieval fuzzy sets web searching OWA aggregationPreview
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References
- [1]Yager, R. R., “Approximate reasoning as a basis for computing with words,” in Computing with Words in Information/Intelligent Systems 1, edited by Zadeh, L. A. and Kacprzyk, J., Springer-Verlag: Heidelberg, 50–77, 1999.Google Scholar
- [2]Zadeh, L. A., “Fuzzy logic = computing with words,” IEEE Transactions on Fuzzy Systems 4, 103–111, 1996.CrossRefGoogle Scholar
- [3]Yager, R. R., “On ordered weighted averaging aggregation operators in multi-criteria decision making,” IEEE Transactions on Systems, Man and Cybernetics 18, 183–190, 1988.MathSciNetMATHCrossRefGoogle Scholar
- [4]Yager, R. R. and Kacprzyk, J., The Ordered Weighted Averaging Operators: Theory and Applications, Kluwer: Norwell, MA, 1997.CrossRefGoogle Scholar
- [5]Zadeh, L. A., “A computational approach to fuzzy quantifiers in natural languages,” Computing and Mathematics with Applications 9, 149–184, 1983.MathSciNetMATHCrossRefGoogle Scholar
- [6]Yager, R. R., “Families of OWA operators,” Fuzzy Sets and Systems 59, 125–148, 1993.MathSciNetMATHCrossRefGoogle Scholar
- [7]Yager, R. R., “On the inclusion of importances in OWA aggregations,” in The Ordered Weighted Averaging Operators: Theory and Applications, edited by Yager, R. R. and Kacprzyk, J., Kluwer Academic Publishers: Norwell, MA, 41–59, 1997.CrossRefGoogle Scholar
- [8]Larsen, H. L. and Yager, R. R., “The use of fuzzy relational thesauri for classifactory problem solving in information retrieval and expert systems,” IEEE Transactions on Systems, Man and Cybernetics 23, 31–41, 1993.MATHCrossRefGoogle Scholar
- [9]Yager, R. R. and Filev, D. P., Essentials of Fuzzy Modeling and Control, John Wiley: New York, 1994.Google Scholar
- [10]Zadeh, L. A., “A new direction in AI — toward a computational theory of perceptions,” AI Magazine Vol 22, No 1, Spring, 73–84, 2001.Google Scholar
- [11]Mitchell, H. B. and Estrakh, D. D., “An OWA operator with fuzzy ranks,” International Journal of Intelligent Systems 13, 69–81, 1998.Google Scholar
- [12]Zadeh, L., “The concept of a linguistic variable and its application to approximate reasoning: Part 1,” Information Sciences 8, 199–249, 1975.MathSciNetMATHCrossRefGoogle Scholar
- [13]Dubois, D. and Prade, H., “Operations on fuzzy numbers,” International Journal of Systems Science 9, 613 – 626, 1978.MathSciNetMATHCrossRefGoogle Scholar
- [14]Yager, R. R., “A procedure for ordering fuzzy subsets of the unit interval,” Information Sciences 24, 143–161, 1981.MathSciNetMATHCrossRefGoogle Scholar
- [15]Yager, R. R. and Filev, D. P., “On the issue of defuzzification and selection based on a fuzzy set,” Fuzzy Sets and Systems 55, 255–272, 1993.MathSciNetMATHCrossRefGoogle Scholar
- [16]Yager, R. R. and Filev, D. P., “Induced ordered weighted averaging operators,” IEEE Transaction on Systems, Man and Cybernetics 29, 141–150, 1999.CrossRefGoogle Scholar
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