Conference proceeding
Measuring Similarity in Description Logics Using Refinement Operators
CASE-BASED REASONING RESEARCH AND DEVELOPMENT, ICCBR 2011, v 6880, pp 289-303
01 Jan 2011
Abstract
Similarity assessment is a key operation in many artificial intelligence fields, such as case-based reasoning, instance-based learning, ontology matching, clustering, etc. This paper presents a novel measure for assessing similarity between individuals represented using Description Logic (DL). We will show how the ideas of refinement operators and refinement graph, originally introduced for inductive logic programming, can be used for assessing similarity in DL and also for abstracting away from the specific DL being used. Specifically, similarity of two individuals is assessed by first computing their most specific concepts, then the least common subsumer of these two concepts, and finally measuring their distances in the refinement graph.
Metrics
Details
- Title
- Measuring Similarity in Description Logics Using Refinement Operators
- Creators
- Antonio A. Sanchez-Ruiz - SoftwareSantiago Ontanon - Universidad Complutense de MadridPedro Antonio Gonzalez-Calero - Univ Complutense Madrid, Dep Ingn Software & Inteligencia Artificial, E-28040 Madrid, SpainEnric Plaza - Artificial Intelligence Research Institute
- Contributors
- A Ram (Editor)N Wiratunga (Editor)
- Publication Details
- CASE-BASED REASONING RESEARCH AND DEVELOPMENT, ICCBR 2011, v 6880, pp 289-303
- Series
- Lecture Notes in Artificial Intelligence
- Publisher
- Springer Nature
- Number of pages
- 3
- Grant note
- TIN2009-13692-C03-01 / Spanish Ministry of Science; Ministry of Science and Innovation, Spain (MICINN); Spanish Government TIN2009-13692-C03-03 / Education project Next-CBR
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science (Computing)
- Web of Science ID
- WOS:000306342100022
- Scopus ID
- 2-s2.0-84856862427
- Other Identifier
- 991021869010304721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Information Systems