Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Semantic and schematic similarities between database objects: a context-based approach
The VLDB Journal — The International Journal on Very Large Data Bases
An Approach for Measuring Semantic Similarity between Words Using Multiple Information Sources
IEEE Transactions on Knowledge and Data Engineering
Using corpus statistics and WordNet relations for sense identification
Computational Linguistics - Special issue on word sense disambiguation
Semantic similarity methods in wordNet and their application to information retrieval on the web
Proceedings of the 7th annual ACM international workshop on Web information and data management
The Google Similarity Distance
IEEE Transactions on Knowledge and Data Engineering
SemreX: Efficient search in a semantic overlay for literature retrieval
Future Generation Computer Systems
SECCO: On Building Semantic Links in Peer-to-Peer Networks
Journal on Data Semantics XII
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
OSS: a semantic similarity function based on hierarchical ontologies
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
A semantic similarity metric combining features and intrinsic information content
Data & Knowledge Engineering
Comparing XML files with a DOGMA ontology to generate Ω-RIDL annotations
OTM'11 Proceedings of the 2011th Confederated international conference on On the move to meaningful internet systems
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Semantic similarity between words aims at establishing resemblance by interpreting the meaning of the words being compared. The Semantic Web can benefit from semantic similarity in several ways: ontology alignment and merging, automatic ontology construction, semantic-search, to cite a few. Current approaches mostly focus on computing similarity between nouns. The aim of this paper is to define a framework to compute semantic similarity even for other grammar categories such as verbs, adverbs and adjectives. The framework has been implemented on top of WordNet. Extensive experiments confirmed the suitability of this approach in the task of solving English tests.