A fuzzy document retrieval system using the keyword connection matrix and a learning method
Fuzzy Sets and Systems - Special issue on applications of fuzzy systems theory, Iizuka '88
Modern Information Retrieval
Fuzzy Relational Images in Computer Science
ReIMICS '01 Revised Papers from the 6th International Conference and 1st Workshop of COST Action 274 TARSKI on Relational Methods in Computer Science
Ontological Engineering
A review of ontology based query expansion
Information Processing and Management: an International Journal
An Index Structure To Retrieve Documents With Geographic Information
DEXA '07 Proceedings of the 18th International Conference on Database and Expert Systems Applications
Query expansion through geographical feature types
Proceedings of the 4th ACM workshop on Geographical information retrieval
Ontology-Based spatial query expansion in information retrieval
OTM'05 Proceedings of the 2005 OTM Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, COA, and ODBASE - Volume Part II
An intelligent information retrieval approach based on two degrees of uncertainty fuzzy ontology
Advances in Fuzzy Systems - Special issue on Fuzzy Functions, Relations, and Fuzzy Transforms: Theoretical Aspects and Applications to Fuzzy Systems
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Many documents stored in digital libraries and document database include geographic references within their texts typically by means of place names. These geographic references can be associated to knowledge to help improve related retrieved documents. For example, in a meteorological document collection the climate knowledge can be associated to the geographic references allowing the retrieval of relevant climate or geographic related documents to an initial user query. In order to explore these issues this work describes a framework to encode a geographic knowledge base composed of multiple related ontologies whose relationships are expressed as fuzzy relations. Each ontology represents a distinct area of the knowledge domain related to geographic references. This knowledge organization is used in a fuzzy method to expand the user initial query. Each ontology can be represented independently as well as their relationships. The fuzzy query expansion method is tested with the Apache Lucene search engine improving the precision measure.