Generality in artificial intelligence
Communications of the ACM
Naive physics I: ontology for liquids
Readings in qualitative reasoning about physical systems
Coordinating context building in heterogeneous information systems
Journal of Intelligent Information Systems - Special issue on next generation information technologies
Context-mediated behavior for intelligent agents
International Journal of Human-Computer Studies - Special issue: using context in applications
Database abstractions: aggregation and generalization
ACM Transactions on Database Systems (TODS)
Naive Semantics for Natural Language Understanding
Naive Semantics for Natural Language Understanding
Interconnecting Heterogeneous Information Systems
Interconnecting Heterogeneous Information Systems
A Unified Approach to Automatic Indexing and Information Retrieval
IEEE Expert: Intelligent Systems and Their Applications
Asessing Semnatic Similarities among Geospatial Feature Class Definitions
INTEROP '99 Proceedings of the Second International Conference on Interoperating Geographic Information Systems
Semantic and schematic similarities between database objects: a context-based approach
The VLDB Journal — The International Journal on Very Large Data Bases
A Knowledge-Based Approach to Querying Heterogeneous Databases
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
Geospatial semantics: why, of what, and how?
Journal on Data Semantics III
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This paper presents a practical application of context for the evaluation of semantic similarity. The work is based on a new model for the assessment of semantic similarity among entity classes that satisfies cognitive properties of similarity and integrates contextual information. The semantic similarity model represents entity classes by their semantic relations (is-a and part-whole) and their distinguishing features (parts, functions, and attributes). Context describes the domain of an application that is determined by the user's intended operations. Contextual information is specified by a set of tuples over operations associated with their respective entity-class arguments. Based on the contextual information, a partial word-sense disambiguation can be achieved and the relevance of distinguishing features for the similarity assessment is calculated in terms of the features' contribution to the characterization of the application domain.