P-TRIAR: Personalization Based on TRIadic Association Rules

被引:0
|
作者
Ali, Selmane Sid [1 ]
Boussaid, Omar [1 ]
Bentayeb, Fadila [1 ]
机构
[1] Univ Lyon 2, Lab ERIC, Bron, France
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article describes a new personalization process on decisional queries through a new approach of triadic association rules mining. This process uses the query log files of users and models them in new way by taking into account their triadic aspect. To validate our approach, we developed a personalization software prototype P-TRIAR (Personalization based on TRIadic Association Rules) which extracts two types of rules from query log files. The first one will serve to query recommendation by taking into account the collaborative aspect of users during their decisional analysis. The second type of rules will enrich user queries. The approach is tested on a real data warehouse to show the compactness of triadic association rules and the refined personalization which we propose.
引用
收藏
页码:234 / 247
页数:14
相关论文
共 50 条
  • [1] P-TRIAR: Personalization based on TRIadic association rules
    Ali, Selmane Sid
    Boussaid, Omar
    Bentayeb, Fadila
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, 8716 : 234 - 247
  • [2] Web Page Personalization based on Weighted Association Rules
    Forsati, R.
    Meybodi, M. R.
    Neiat, A. Ghari
    ICECT: 2009 INTERNATIONAL CONFERENCE ON ELECTRONIC COMPUTER TECHNOLOGY, PROCEEDINGS, 2009, : 130 - +
  • [3] Computing triadic generators and association rules from triadic contexts
    Rokia Missaoui
    Pedro H. B. Ruas
    Léonard Kwuida
    Mark A. J. Song
    Mohamed Hamza Ibrahim
    Annals of Mathematics and Artificial Intelligence, 2022, 90 : 1083 - 1105
  • [4] Computing triadic generators and association rules from triadic contexts
    Missaoui, Rokia
    Ruas, Pedro H. B.
    Kwuida, Leonard
    Song, Mark A. J.
    Ibrahim, Mohamed Hamza
    ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE, 2022, 90 (11-12) : 1083 - 1105
  • [5] Mining Triadic Association Rules from Ternary Relations
    Missaoui, Rokia
    Kwuida, Leonard
    FORMAL CONCEPT ANALYSIS, 2011, 6628 : 204 - 218
  • [6] Towards Collaborative Multidimensional Query Recommendation with Triadic Association Rules
    Selmane, Sid Ali
    Boussaid, Omar
    Bentayeb, Fadila
    INTERNATIONAL JOURNAL OF DECISION SUPPORT SYSTEM TECHNOLOGY, 2015, 7 (03) : 17 - 35
  • [7] Association-Rules-Based Recommender System for Personalization in Adaptive Web-Based Applications
    Mican, Daniel
    Tomai, Nicolae
    CURRENT TRENDS IN WEB ENGINEERING, 2010, 6385s : 85 - 90
  • [8] Using back-propagation to learn association rules for service personalization
    Huang, Yo-Ping
    Chuang, Wei-Po
    Ke, Ya-Hui
    Sandnes, Frode-Elka
    EXPERT SYSTEMS WITH APPLICATIONS, 2008, 35 (1-2) : 245 - 253
  • [9] Exception rules mining based on negative association rules
    Daly, O
    Taniar, D
    COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2004, PT 4, 2004, 3046 : 543 - 552
  • [10] An Association Rules and Sequential Rules Based Recommendation System
    Liao, Shu
    Zou, Tengyue
    Chang, Huiyou
    2008 4TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-31, 2008, : 11144 - 11147