Ghanshyam Singh Thakur

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This paper presents new approach, Hesitant Distance Similarity Measures for Document Clustering. The proposed Hesitant Distance Similarity Measures approach is based on Fuzzy Hesitant Sets. In this paper we have used fifty Similarity Measures from f1 to f50. The steps, Document collection, Text Pre-processing, Feature Selection, Indexing, Clustering Process(More)
In this study we investigate the significance of textual document which is now commonly recognized by researchers for better management, smart navigation, well-organized filtering, and finding the results. The challenging part is to extract the meaningfulness and to manage the purpose of the " best " Mining Rule .This research study is proposed to refine(More)
Clustering is one of the very important technique used for classification of large dataset and widely applied to many applications including analysis of social networking sites, aircraft accidental, company performance etc. In recent days, Communication, advertising through social networking sites are most popular and interactive strategy among the users.(More)
The self-control study on thirty normal subjects of both genders (mean age 25.83 +/- 3.41 years) were taken in a self control study group and were tested for three types of Nostril breathing practices and Breath Awareness (BA) effects. Namely verbal recall performance of numerical data such as Digit Span Forward (DSF) and Digit Span Backward (DSB) as well(More)
Frequent pattern mining is one of the most important research topics for many real life applications in the area of data mining. Frequent item set originates from association rule mining that uses to find association rules of items in large transactional database. Many existing algorithm to mine for the frequent itemset from static transaction database that(More)