Mining web log data for personalized recommendation system

Asma Rosyidah, Isti Surjandari Prajitno, Zulkarnain

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Increase in number of internet users in Indonesia boosts the development of e-commerce platform. Whereas potential access to a larger and more diverse customer base is generally viewed as an opportunity, it can also represent increase in competition among e-commerce platforms. Hence, e-commerce needs to develop sophisticated strategies to attract and retain customers, one of which is done through personalization in web services. Recommendation system, one form of web service personalization in e-commerce platform, predicts user preferences and helps them find products that they may be interested in by implementing web mining techniques. This empirical research investigated user web log data which illustrate behavior and implicit preferences of customers in one of ecommerce in Indonesia to predict user preferred product category in their future request. In this study, model-based recommendation system was built based on users' activity in a session and site type using C5.0 algorithm of decision tree technique. Top N recommendations were given based on probability-based ranking of categories resulted from probability estimation of the decision tree.

Original languageEnglish
Title of host publication2018 6th International Conference on Information and Communication Technology, ICoICT 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages441-446
Number of pages6
ISBN (Electronic)9781538645710
DOIs
Publication statusPublished - 8 Nov 2018
Event6th International Conference on Information and Communication Technology, ICoICT 2018 - Bandung, Indonesia
Duration: 3 May 20184 May 2018

Publication series

Name2018 6th International Conference on Information and Communication Technology, ICoICT 2018

Conference

Conference6th International Conference on Information and Communication Technology, ICoICT 2018
CountryIndonesia
CityBandung
Period3/05/184/05/18

Keywords

  • Decision tree C5.0
  • E-commerce
  • Personalization
  • Recommendation system
  • Web log
  • Web mining

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