Clustering Improvement in Homonym Detection using Concept Based Document Similarity with Conceptual Term Frequency Analysis
Keywords:
Concept based Document Similarity, Homonym Words, Clustering, EntropyAbstract
The homonym words have the same spelling but have different meanings and these words found in almost every language. The homonyms are a source of noise in most text analysis and are difficult to detect. It essentially understands to make correspond to combinations of identifying / difference in parameters like sound, writing, and meaning, according to how the terms are traditionally used; the combination of same sound, same spelling, but distinct meaning is for homonyms. The paper presents a clustering improvement analysis using concept based document similarity method for homonym recognition based on concept based document similarity, which allows a word to be comprehended based on its context. The results show the proposed method shows better performance in clustering improvement and entropy calculation.
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