• Shivangi Sane
• Prof. Dr. Mrs. S. A.Itkar

In Present World’s competitive business, the achievements is totally in light of capacity to make things more engaging to clients than the oppositions. Data Mining approach for identifying and monitoring firm’s competitors and to solve number of question like standardizing and quantifying the competitiveness between two items, finding the main contenders of given item And the features of item are effective or not, finding competitiveness between two items based on the market segments that they can both cover is calculated here. By obtaining a wide source of information and customer reviews,the new formalization of the competitiveness between two items based on market segments that they can both cover, is made. Proficient strategies for assessing aggressiveness in extensive audit datasets and address the regular issue of finding the best k contenders of a given thing. Our assessment of aggressiveness uses client surveys, a plenteous well-spring of data that is accessible in an extensive variety of spaces. We display proficient strategies for assessing intensity in huge survey datasets and address the characteristic issue of finding the best k competitors of a given item.

Data mining, Web mining, Information Search and Retrieval.

"EFFICIENT HYBRID ALGORITHM FOR HIGH UTILITY ITEMSET MINING.Mining Competitor from Large Unstructured Data sets using C Miner", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.409-413, June 2019, Available :http://www.jetir.org/papers/JETIR1906L60.pdf

"EFFICIENT HYBRID ALGORITHM FOR HIGH UTILITY ITEMSET MINING.Mining Competitor from Large Unstructured Data sets using C Miner", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp409-413, June 2019, Available at : http://www.jetir.org/papers/JETIR1906L60.pdf