Incorporating Generalized Quantifiers into Description Logic to Improve Source Selection

35 Pages Posted: 2 Oct 2001

See all articles by Stuart Madnick

Stuart Madnick

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Steven Y. Tu

Soochow University

Date Written: June 2001

Abstract

Source selection allows the users to express what they want while the system automatically performs the identification and selection of relevant sources to answer the query request. To automate that process, the system must be able to represent the contents of data sources in a description language. Descriptions of source contents can be characterized by the two concepts of scope and size. This paper builds upon and extends the concept language, description logic (DL), to propose a novel representation system to achieve that goal. We point out that there are technical barriers within description logic limiting the types of data sources that can be represented. Specifically, we show that (1) DL is awkward in representing sufficient conditions, and (2) DL can describe properties of a concept itself only in the case of existential quantification. These barriers limit expressions of size information in source descriptions and thus cause us to extend DL with the notion of generalized quantifiers to make them inter-operable with traditional logic. The proposed formalism integrates the nice features of generalized quantifiers into description logic, and hence achieves more expressive power than previous representation systems based purely on description logic. It is also shown that the proposed language preserves those mathematical properties that traditional logic-based formalisms are known to hold.

Suggested Citation

Madnick, Stuart E. and Tu, Steven Yi-Cheng, Incorporating Generalized Quantifiers into Description Logic to Improve Source Selection (June 2001). MIT Sloan Working Paper No. 4170; CISL Working Paper No. 01-07. Available at SSRN: https://ssrn.com/abstract=281842 or http://dx.doi.org/10.2139/ssrn.281842

Stuart E. Madnick (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

E53-321
Cambridge, MA 02142
United States
617-253-6671 (Phone)
617-253-3321 (Fax)

Steven Yi-Cheng Tu

Soochow University ( email )

No. 1 Shizi Street
Taipei, Jiangsu 215006
Taiwan

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