Development of Fuzzy Based Categorical Text Clustering Algorithm for Information Retrieval

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Provided by: The International Journal of Innovative Research in Computer and Communication Engineering
Topic: Big Data
Format: PDF
Similarities play a vital role in clustering text on the prediction, in order to produce an efficient result when compared to the existing algorithms like k-modes, rock and stirr. Future selection is important for making a subset according to the dataset. In order to overcome the problems in the existing system, single cluster and multiple clustering methods are proposed in order to cluster the famous quotes with multiple semantic associations. But the problems on overlapping between the quotes are analyzed and the sentence similarities for information retrieval are measured.
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