Advertisement

Machine Learning Approach to Recommender System for Web Mining

  • Jagdeep KaurEmail author
  • Jatinder Singh BalEmail author
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 38)

Abstract

One of the major challenges face by webmasters is the introduction of numerous choices to the customer, which leads to repetitive and difficulty in locating the correct item or data on the webpage. In the traditional approach, if the data was changed, pooling approach was possible, only if data variation was within the cluster information. In case the data exceeds the limit, classification was difficult to perform. Therefore, we need to have a classification approach that can work under these conditions. In the proposed work we have implemented Hybrid of ANN and KNN approach and found improvement in the recommendation system with greater accuracy.

Keywords

Web mining Artificial Neural Network Genetic Algorithm Artificial Intelligence Information mining 

References

  1. 1.
    Talakokkula, A.: A survey on web usage mining, applications and tools. Comput. Eng. Intell. Syst. 6, 22–30 (2015)Google Scholar
  2. 2.
    Kosala, R., Blockeel, H.: Web mining research: a survey. ACM SIGKDD Explor. Newsl. 2, 1–15 (2000)CrossRefGoogle Scholar
  3. 3.
    Rana, C.: A study of web usage mining research tools. IJANA 3, 1422–1429 (2012)Google Scholar
  4. 4.
    Chavda, S.: Recent trends and novel approaches in web usage mining. Int. Res. J. Eng. Technol. (IRJET) 4, 1319–1322 (2017)Google Scholar
  5. 5.
    Kaur, J., Singh, J.: Particle swarm optimization based neural network. Int. J. Emerg. Technol. Eng. Res. 3, 5–12 (2015)Google Scholar
  6. 6.
    Kumar, P., Sharma, P.: Artificial neural networks-a study. Int. J. Emerg. Eng. Res. Technol. 2, 143–148 (2014)Google Scholar
  7. 7.
    Imandoust, S.B., Bolandraftar, M.: Application of K-Nearest Neighbor (KNN) approach for predicting economic events: theoretical background. Int. J. Eng. Res. Appl. 3, 605–610 (2013)Google Scholar
  8. 8.
    Deepashri, K.S., Kamath, A.: Survey on techniques of data mining and its applications. Int. J. Emerg. Res. Manag. Technol. 6, 198–201 (2017)Google Scholar
  9. 9.
    Kaur, J.: Recommendation system with Automated Web Usage data mining by using k-Nearest Neighbour (KNN) classification and artificial neural network (ANN) algorithm. Int. J. Res. Appl. Sci. Eng. Technol. 8, 160–168 (2017)Google Scholar
  10. 10.
    Adeniyi, D.A.: Automated Web usage data mining and recommendation system using K-Nearest Neighbor classification method. Appl. Comput. Inf. 12, 90–108 (2016)Google Scholar
  11. 11.
    Call, J.M.: Genetic algorithms for modelling and optimization. J. Comput. Appl. Math. 184, 205–222 (2005)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Nazeer, F., Nazeer, N., Akbar, I.: Data visualization techniques – a survey. Int. J. Res. Emerg. Sci. Technol. 4, 4–8 (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringSant Baba Bhag Singh UniversityJalandharIndia

Personalised recommendations