A Logic for Concepts and Similarity

Categorisation of objects into classes is currently supported by (at least) two ‘orthogonal’ methods. In logic-based approaches, classifications are defined through ontologies or knowledge bases which describe the existing relationships among terms. Description logic (DL) has become one of the most successful formalisms for representing such knowledge bases, in particular because theoretically well-founded and efficient reasoning tools have been readily available. In numerical approaches, classifications are obtained by first computing similarity (or proximity) measures between objects and then categorising them into classes by means of Voronoi tessellations, clustering algorithms, nearest neighbour computations, etc. In many areas such as bioinformatics, computational linguistics or medical informatics, these two methods have been used independently of each other: although both of them are often applied to the same domain (and even by the same researcher), up to now no formal...

• Type: Journal
• Year: 2007
• Where: LOGCOM
• Authors: Mikhail Sheremet, Dmitry Tishkovsky, Frank Wolter, Michael Zakharyaschev
• Keywords: Knowledge Base, LOGCOM 2007, Reasoning Tools, first Computing Similarity