Extracting top competitors from unorganized data-Review
International Research Journal on Advanced Science Hub,
2019, Volume 1, Issue 1, Pages 10-16
10.47392/irjash.2019.02
Abstract
The ability to make a product more desirable to consumers than competition is central to the success of every competitive business. The web application allows the user to see products and their functionalities together with the potential to comment on the product and can also show other customers ' comments. A potential customer finds it difficult to read and determine from the broad comments. The competition of two items based upon market segments that both can cover is determined by this approach. A "CMiner" algorithm is provided to find the top competitors for a particular item to predict competition using the customer reviews. This system returns the competitors of products correctly and reliably, as compared to previous models based on subjective and comparative Web expressions. Business organizations are not only able to identify competitiveness, but they are also able to benefit from meeting user needs.[1] George Valkanas, Theodoros Lappas, and Dimitrios Gunopulos,” Mining Competitors from Large Unstructured Datasets”, IEEE Transactions on Knowledge and Data Engineering, 1041-4347 (c) 2016
[2] M. Bergen and M. A. Peteraf, “Competitor identification and competitor analysis: a broad-based managerial approach,” Managerial and Decision Economics, 2002.
[3] R. Li, S. Bao, J. Wang, Y. Yu, and Y. Cao, “Cominer: An effective algorithm for mining competitors from the web,” in ICDM, 2006
[4] Kunpeng Zhang,Ramanathan Narayanan,” Voice of the Customer: Mining Online Customer Reviews for Product-Feature Based Ranking”
[5] Kunpeng,Zhang,Yu,Cheng,WeiKang,Liao,Alok,Choudhary,”Mining Millions of Reviews : A Technique to Rank Products Based on Importance of Reviews”
[6] E. Marrese-Taylor, J. D. Vel´asquez, F. Bravo-Marquez, and Y. Matsuo,“Identifying customer preferences about tourism products using an aspectbased opinion mining approach,” Procedia Computer Science, vol. 22, pp. 182–191, 2013
[7] T.-N. Doan, F. C. T. Chua, and E.-P. Lim, “Mining business competitiveness from user visitation data,” in International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction. Springer, 2015, pp. 283–289.
- Article View: 165
- PDF Download: 161