SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
Wikify!: linking documents to encyclopedic knowledge
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Learning to link with wikipedia
Proceedings of the 17th ACM conference on Information and knowledge management
WikiRelate! computing semantic relatedness using wikipedia
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
A generalized method for word sense disambiguation based on wikipedia
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
InferenceNet.Br: expression of inferentialist semantic content of the Portuguese language
PROPOR'10 Proceedings of the 9th international conference on Computational Processing of the Portuguese Language
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A promising approach to cope with the challenges that Word Sense Disambiguation brings is to use knowledge-intensive methods. Typically they rely on Wikipedia for supporting automatic concept identification. The exclusive use of Wikipedia as a knowledge base for word disambiguation and therefore the general identification of topics, however, have low accuracy vis-à-vis texts with diverse topics, as can be the case with blogs. This motivated us to propose a method for word disambiguation that, in addition to the use of Wikipedia, uses a common sense database. Use of this base enriches the definition of the concepts previously identified with the help of Wikipedia, and permits the definition of a similarity measure between concepts, which is characterized by verifying the similarity of two concepts from the viewpoint of conceptual proximity in the Wikipedia hierarchy, in addition to the proximity between such concepts in terms of the inferences that they can make. We show that by doing this, we improved the accuracy of automatic disambiguation of words compared with methods that do not use a common sense base.