Authors:
Arijit De
1
and
Elizabeth Diaz
2
Affiliations:
1
Tata Consultancy Services, India
;
2
University of Texas- Permian Basin, United States
Keyword(s):
Information Retrieval, Fuzzy Sets, Soft Computing, Multi-criteria Decision Making.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Fuzzy Information Retrieval and Data Mining
;
Fuzzy Systems
;
Fuzzy Systems Design, Modeling and Control
;
Soft Computing
;
Soft Computing and Intelligent Agents
Abstract:
Search Engines are tools for searching the World Wide Web or any other large data collection. Search engines typically accept a user query and returns a list of relevant documents. These documents are generally returned as a result list for the user to see. A metasearch engine is a tool that allows an information seeker to search information on the world wide web through multiple search engines. A key function of a metasearch engine is to aggregate search results returned by many search engines. Result aggregation is an important task for a metasearch engine. In this paper we propose a model for result aggregation for metasearch, Fuzzy ANP, that employs fuzzy linguistic quantifier guided approach to result merging using Saty's Analytical Network Process. We compare our model to two existing result merging models, the Borda Fuse model and the OWA model for metasearch. Our results show that our model outperforms the OWA model and Borda-Fuse model significantly.