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Abstract
The need for an effective text similarity measures has led many previous studies to propose different text weighting schemes to enhance the overall performance of sentence similarity measures. Term Frequency Inverse Document Frequency (TF-IDF) is a weighting method that is commonly used to determine the occurrence of a term/word in a document. This paper proposes the use of Noun Phrase (NP) based TF-IDF weighting scheme in order to empower the efficiency of text similarity. A total of eight pairs of statements were used to validate the proposed method. The obtained results were then compared with the standard TF-IDF weighting scheme. The result shows that NP-TF-IDF has significantly improved the performance of text similarity measures as compared to the standard TF-IDF. Our findings may offer the necessary insights related to the development of text similarity applications.
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