@inproceedings{2bc99f0357ec49d782ba374f39bd59eb,
title = "Mining fuzzy ontology for a web-based granular information retrieval system",
abstract = "This paper illustrates the design and development of a fuzzy-ontology based granular IR system to facilitate domain specific search. Based on the notion of information granulation, a novel computational model is developed to estimate the granularity of documents and rank these documents according to the information seekers' specific granularity requirements. The initial experiments confirm that our granular IR system outperforms a vector space based IR system for domain specific search. Our research work opens the door to the application of granular computing methodology to enhance domain specific search on the Internet. {\textcopyright} 2009 Springer Berlin Heidelberg.",
keywords = "Fuzzy Domain Ontology, Fuzzy Subsumption, Granular Computing, Granular IR Systems, Information Retrieval",
author = "Lau, \{Raymond Y. K.\} and Lai, \{Chapmann C. L.\} and Yuefeng Li",
year = "2009",
doi = "10.1007/978-3-642-02962-2\_30",
language = "English",
isbn = "3642029612",
volume = "5589 LNAI",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "239--246",
booktitle = "Rough Sets and Knowledge Technology",
address = "Germany",
note = "4th International Conference on Rough Sets and Knowledge Technology, RSKT 2009 ; Conference date: 14-07-2009 Through 16-07-2009",
}