Abstract
Classical description logics are limited in dealing with the crisp concepts and relationships, which makes it difficult to represent and process imprecise information in real applications. In this paper we present a type-2 fuzzy version of \(\mathcal{ALC}\) and describe its syntax, semantics and reasoning algorithms, as well as the implementation of the logic with type-2 fuzzy OWL. Comparing with type-1 fuzzy \(\mathcal{ALC}\), system based on type-2 fuzzy \(\mathcal{ALC}\) can define imprecise knowledge more exactly by using membership degree interval. To evaluate the ability of type-2 fuzzy \(\mathcal{ALC}\) for handling vague information, we apply it to semantic search engine for building the fuzzy ontology and carry out the experiments through comparing with other search schemes. The experimental results show that the type-2 fuzzy \(\mathcal{ALC}\) based system can increase the number of relevant hits and improve the precision of semantic search engine.
This work is supported by National Natural Science Foundation of China under Grant 60403027, Natural Science Foundation of Hubei Province under Grant 2005ABA258, Open Foundation of State Key Laboratory of Software Engineering under Grant SKLSE05-07, and a grant from Huawei Technologies Co., Ltd.
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Li, R., Sun, X., Lu, Z., Wen, K., Li, Y. (2007). Towards a Type-2 Fuzzy Description Logic for Semantic Search Engine. In: Dong, G., Lin, X., Wang, W., Yang, Y., Yu, J.X. (eds) Advances in Data and Web Management. APWeb WAIM 2007 2007. Lecture Notes in Computer Science, vol 4505. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72524-4_82
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DOI: https://doi.org/10.1007/978-3-540-72524-4_82
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