Abstract
When a traditional forward dictionary maps words to their definitions, a reverse dictionary takes a user input phrase with a specific concept, and returns a set of candidate words closely related to the input phrase provided. This application works worthy not only for the general public, but also to those who work personally with words. Upon receiving a search concept, the Reverse Dictionary consults the forward dictionary and selects those words whose definitions are similar to the given concept. And thus it is reduced to a concept similarity problem. The semantic similarity between concepts is a method to measure the semantic connection, or the semantic distance between two concepts according to a given ontology. The experimental results shows that the approach used here provides significant performance without losing the quality of the result.
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