Word sense disambiguation for free-text indexing using a massive semantic network
CIKM '93 Proceedings of the second international conference on Information and knowledge management
Experiments on using semantic distances between words in image caption retrieval
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Navigation via similarity: automatic linking based on semantic closeness
Information Processing and Management: an International Journal - Special issue: methods and tools for the automatic construction of hypertext
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Semantic classes and syntactic ambiguity
HLT '93 Proceedings of the workshop on Human Language Technology
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
Representation and Management of Narrative Information: Theoretical Principles and Implementation
Representation and Management of Narrative Information: Theoretical Principles and Implementation
WikiRelate! computing semantic relatedness using wikipedia
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Threading facts into a collective narrative world
ICIDS'10 Proceedings of the Third joint conference on Interactive digital storytelling
Propagating user interests in ontology-based user model
AI*IA'11 Proceedings of the 12th international conference on Artificial intelligence around man and beyond
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Recent extensive usage of ontologies as knowledge bases that enable rigorous representation and reasoning over heterogenous data poses certain challenges in their construction and maintenance. Many of these ontologies are incomplete, containing many dense sub-ontologies. A need arises for a measure that would help calculate the similarity between the concepts in these kinds of ontologies. In this work, we introduce a new similarity measure for ontological concepts that takes these issues into account. It is based on conceptual specificity, which measures how much a certain concept is relevant in a given context, and on conceptual distance, which introduces different edge lengths in the ontology graph. We also address the problem of computing similarity between concepts in the presence of implicit classes in ontologies. The evaluation of our approach shows an improvement over Leacock and Chodorow's distance based measure. Finally, we provide two application domains which can benefit when this similarity measure is used.