Research on personalized recommendation in E-commerce service based on data mining

Tao Xu, Jing Tian, Tomohiro Murata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We propose a new hybrid recommendation algorithm to optimization the cold-start problem with Collaborative Filtering (CF). And we use neighborhood-based collaborative filtering algorithm has obtained great favor due to simplicity, justifiability, and stability. However, when faced with large-scale, sparse, or noise affected data, nearest-neighbor collaborative filtering performs not so well, as the calculation of similarity between user or item pairs is costly and the accuracy of similarity can be easily affected by noise and sparsity. We introduce a new model comprising both In the training stage, user-item and film-item relationships in recommender systems, and describe how to use algorithm generates recommendations for cold-start items based on the preference model. Our experiments model provides a relatively efficient and accurate recommendation technique.

Original languageEnglish
Title of host publicationLecture Notes in Engineering and Computer Science
Pages313-317
Number of pages5
Volume1
Publication statusPublished - 2013
EventInternational MultiConference of Engineers and Computer Scientists 2013, IMECS 2013 - Kowloon
Duration: 2013 Mar 132013 Mar 15

Other

OtherInternational MultiConference of Engineers and Computer Scientists 2013, IMECS 2013
CityKowloon
Period13/3/1313/3/15

Fingerprint

Collaborative filtering
Electronic commerce
Data mining
Recommender systems
Experiments

Keywords

  • Cold-s tart
  • Collaborative Filtering
  • Data mining
  • Data sparsity
  • Recommender system

ASJC Scopus subject areas

  • Computer Science (miscellaneous)

Cite this

Xu, T., Tian, J., & Murata, T. (2013). Research on personalized recommendation in E-commerce service based on data mining. In Lecture Notes in Engineering and Computer Science (Vol. 1, pp. 313-317)

Research on personalized recommendation in E-commerce service based on data mining. / Xu, Tao; Tian, Jing; Murata, Tomohiro.

Lecture Notes in Engineering and Computer Science. Vol. 1 2013. p. 313-317.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Xu, T, Tian, J & Murata, T 2013, Research on personalized recommendation in E-commerce service based on data mining. in Lecture Notes in Engineering and Computer Science. vol. 1, pp. 313-317, International MultiConference of Engineers and Computer Scientists 2013, IMECS 2013, Kowloon, 13/3/13.
Xu T, Tian J, Murata T. Research on personalized recommendation in E-commerce service based on data mining. In Lecture Notes in Engineering and Computer Science. Vol. 1. 2013. p. 313-317
Xu, Tao ; Tian, Jing ; Murata, Tomohiro. / Research on personalized recommendation in E-commerce service based on data mining. Lecture Notes in Engineering and Computer Science. Vol. 1 2013. pp. 313-317
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