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Data Mining and its Various Concepts

8 pagesPublished: October 23, 2018


Information mining is known as the extraction of concealed prescient data from expansive databases whose primary concentration is to enable organizations to concentrate on the most critical data to display in their information stockrooms. Data mining can in like manner be called as the examination of data and the use of the distinctive programming techniques for finding illustrations and regularities in the given courses of action of data. The articulation "Electronic exchange" (or web business) ordinarily implies the usage of an electronic medium to finish all the business trades. Numerous a times it alludes to the offer of items by means of Internet, however it likewise incorporates the acquiring of systems through Internet. This primary concentration of this paper is to give the fundamental presentation about the different information mining methods accessible and furthermore to break down these procedures based on their execution. The paper additionally characterizes the different goals of the information mining in internet business. The paper additionally concentrates on the bunching methods and tries to think about the different grouping procedures.

Keyphrases: Clustering, Data Mining, e-commerce, Web Mining

In: Vinay K Chandna, Vijay Singh Rathore and Shikha Maheshwari (editors). Proceedings on International Conference on Emerging Trends in Expert Applications & Security (2018), vol 2, pages 95--102

BibTeX entry
  author    = {Alisha Sikri and Surjeet Dalal and Netra Pal Singh and Neeraj Dahiya},
  title     = {Data Mining and its Various Concepts},
  booktitle = {Proceedings on International Conference on Emerging Trends in Expert Applications \textbackslash{}\& Security (2018)},
  editor    = {Vinay K Chandna and Vijay Singh Rathore and Shikha Maheshwari},
  series    = {Kalpa Publications in Engineering},
  volume    = {2},
  pages     = {95--102},
  year      = {2018},
  publisher = {EasyChair},
  bibsource = {EasyChair,},
  issn      = {2515-1770},
  url       = {},
  doi       = {10.29007/pq4r}}
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