Application of Data Mining to E-Commerce Recommendation Systems

  • Authors

    • Dr P.V.R.D. Prasad Rao
    • S Varakumari
    • Vineetha B
    • V Satish
    2018-05-31
    https://doi.org/10.14419/ijet.v7i2.32.15730
  • Recommendation, hybrid approach, k-means, apriori algorithm.

  • The rising power of technology has intensely improved the information storage, collection, and manipulation ability. As the information is growing very rapid along with its complexness, data analysis has become more important. The aim of this paper is to recommend products to the user which are more likely to be purchased. This paper, first describes about different techniques for recommendation and the research regarding recommendation system, then suggests a better approach for a good recommendation system and explains the results of that approach. Here, a combination of k-means clustering algorithm and apriori algorithm on transactional dataset so that a better recommendation list can be obtained.

     

  • References

    1. [1] †Dynamic Recommendation System Using Web Usage Mining for E-Commerce usersâ€, Prajyotilopes and BidishaRoy, International Conference on Advanced Computing Technologies and Applications(ICACTA-2015).

      [2] “Survey Paper on Recommendation System using Data Mining Techniquesâ€, Sony V Hovale, Poonam G, International Journal of Engineering and Computer Science (May 2016).

      [3] “A Book Recommender System Using Frequent Pattern Algorithmâ€, Joshua J.V., Alao O.D., Adebayo A.O., Onanuga G.A., Ehinlafa E.O., Ajayi O.E., Journal of Software Engineering and Simulation, Volume 3, Issue 3(2016).

      [4] “A collaborative approach for research paper recommender systemâ€, Haruna K, Akmar Ismail M, Damiasih D,Sutopo J, Herawan T (2017) PLoS ONE 12(10): e0184516.

      [5] †DeepLearning Methods on Recommender System: A Survey of State-of-the-artâ€, Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui, International Journal of Computer Applications (0975 – 8887) (2017).

      [6] “Automated web usage data mining and recommendation system using K-Nearest Neighbor (KNN)classification methodâ€, D.A. Adeniyi, Z. Wai, Y. Yongquan, Applied Computing and Informatics (2014).

      [7] “Algorithms and Methods in Recommender Systemsâ€, Daniar Asanov,Berlin Institute of Technology.

      [8] “Survey on Recommendation System Methodsâ€, Paritosh Nagarnaik, Prof. A.Thomas,Department of Computer Science and Engineering, ICECS 2015.

      [9] “Survey Paper on Wayfarer: A Travel Recommendation Systemâ€, Prof D.D.Gatade, Sanket Jain, Jay Chandarana, Richa Mahajan, Shweta,IJARCCE, Vol. 6, Issue 4, April 2017.

      [10] †A Survey of Collaborative Filtering Algorithms for Social Recommender Systemsâ€, Y.Dou, H.Yang and X.deng,2016 12th International Conference on Semantics, Knowledge and Grids(SKG), Beijing, 2016,pp10-46.

      [11] “How to Develop Online Recommendation Systems that Deliver Superior Business Performanceâ€, Anup Prakash Warade Cognizant Associate, Vignesh Murali Natarajan, Siddharth Sharad Chandak, cognizant 20-20 insights,2012.

      [12] “Real-World Recommender Systems for Academia: The Pain and Gain in Building, Operating, and Researching them “, Joeran Beel and Siddharth Dinesh, the 5th International Workshop on Bibliometric-enhanced Information Retrieval (BIR) (Beel & Dinesh, 2017).

      [13] “User Personality and User Satisfaction with Recommender Systemsâ€, Tien T. Nguyen, F. Maxwell Harper, Loren Terveen, Joseph A. Konstan, Information Systems Frontiers, 2017, Page 1.

      [14] “Two collaborative filtering recommender systems based on sparse dictionary codingâ€, Ismail Emre Kartoglu, Michael W. Spratling, Springer-Verlag London Ltd., part of Springer Nature 2018.

      [15] “Recommender Systems for Large-Scale Social Networks: A review of challenges and solutionsâ€, Magdalini Eirinaki, Jerry Gao, Iraklis Varlamis, Konstantinos Tserpes, Future Generation Computer Systems, Elsevier (2018).

      [16] “Amazon.com Recommendations Item-to-Item Collaborative Filteringâ€, Greg Linden, Brent Smith, and Jeremy York, Published by the IEEE Computer Society 1089-7801/03/$17.00©2003 IEE, IEEE INTERNET COMPUTING.

      [17] “Recommenderlab: A Framework for Developing and testing Recommendation Algorithmsâ€, Mic hael Hahsler, Southern Methodist University.

      [18] “Evaluation of Subspace Cluestering of High Dimensional Dataâ€, V.Kumutha,S.Palaniammal, ACM SIGKDD Explorationa Newsletter-Special issue ion learning from imbalances datasets pgL90-150), (2012).

      [19] “Enhancing Product Recommendation Systems on Sparse Binary Dataâ€, Ayhan.demiriz,Information technology,Verizon Inc., 919 Hidden Ridge,Irving,TX 75038(2004).

      [20] “Towards the Next Generation of Recommender Systems:A Survey of the state-of-the-Art and Possible Extensionsâ€, International Journal of Computer Applications(0975-8887), (2005).

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  • How to Cite

    P.V.R.D. Prasad Rao, D., Varakumari, S., B, V., & Satish, V. (2018). Application of Data Mining to E-Commerce Recommendation Systems. International Journal of Engineering & Technology, 7(2.32), 420-423. https://doi.org/10.14419/ijet.v7i2.32.15730