Mining high utility mobile sequential patterns in mobile commerce environments

Bai En Shie*, Hui Fang Hsiao, S. Tseng, Philip S. Yu

*Corresponding author for this work

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

55 Scopus citations

Abstract

Mining user behaviors in mobile environments is an emerging and important topic in data mining fields. Previous researches have combined moving paths and purchase transactions to find mobile sequential patterns. However, these patterns cannot reflect actual profits of items in transaction databases. In this work, we explore a new problem of mining high utility mobile sequential patterns by integrating mobile data mining with utility mining. To the best of our knowledge, this is the first work that combines mobility patterns with high utility patterns to find high utility mobile sequential patterns, which are mobile sequential patterns with their utilities. Two tree-based methods are proposed for mining high utility mobile sequential patterns. A series of analyses on the performance of the two algorithms are conducted through experimental evaluations. The results show that the proposed algorithms deliver better performance than the state-of-the-art one under various conditions.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 16th International Conference, DASFAA 2011, Proceedings
Pages224-238
Number of pages15
EditionPART 1
DOIs
StatePublished - 28 Apr 2011
Event16th International Conference on Database Systems for Advanced Applications, DASFAA 2011 - Hong Kong, China
Duration: 22 Apr 201125 Apr 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6587 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Database Systems for Advanced Applications, DASFAA 2011
CountryChina
CityHong Kong
Period22/04/1125/04/11

Keywords

  • High utility mobile sequential pattern
  • mobile environment
  • mobility pattern mining
  • utility mining

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