Extracting Top Competitors from Unorganized Data
M. Senthamil Selvi1, P. V. Kavitha2, J. Angel Ida Chellam3
1M. Senthamil Selvi, Professor & Head, Department of Information Technology, Sri Ramakrishna Engineering College, Coimbatore (TamilNadu), India.
2P. V. Kavitha, Assistant Professor, Department of Information Technology, Sri Ramakrishna Engineering College, Coimbatore (TamilNadu), India.
3J. Angel Ida Chellam, Assistant Professor, Department of Information Technology, Sri Ramakrishna Engineering College, Coimbatore (TamilNadu), India.
Manuscript received on 05 March 2019 | Revised Manuscript received on 17 March 2019 | Manuscript Published on 22 March 2019 | PP: 515-519 | Volume-8 Issue-5S April 2019 | Retrieval Number: ES3474018319/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In a competitive business, success factor is based on the ability to make an item more interesting to customers than competition. An E-Commerce application allows the user to view the items and their features along with the option of commenting about the item and can also view comments of other customer. From the large reviews, it is difficult for a customer to make a decision. With the set of items in existing market, competitiveness should be evaluated using the reviews so that manufacturing item is not dominated by other existing items. The proposed novel approach defines the competitiveness between two items based on market segments. A “CMiner” algorithm is used to find the top competitors of a given item using the result of Item dominance. This method improves the quality of the result when compared to previous competitor ranking models based on probability value.
Keywords: Customer Reviews, Competitor Mining, Data Mining, Firm Analysis, Information Search and Retrieval, Item Dominance.
Scope of the Article: Community Information Systems