Prediction of next destinations from irregular patterns

被引：8

作者：

Boukhechba, Mehdi ^{[1
]}

Bouzouane, Abdenour ^{[1
]}

Gaboury, Sebastien ^{[1
]}

Gouin-Vallerand, Charles ^{[2
]}

Giroux, Sylvain ^{[3
]}

Bouchard, Bruno ^{[1
]}

机构：

[1] Univ Quebec Chicoutimi UQAC, LIARA Lab, Chicoutimi, PQ, Canada

[2] Univ Quebec TELUQ, Montreal, PQ, Canada

[3] Univ Sherbrooke, Sherbrooke, PQ, Canada

来源：

JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING | 2018年 / 9卷 / 05期

基金：

加拿大魁北克医学研究基金会;

关键词：

Human activities; Activity prediction; Online association rules; Concept drift;

D O I：

10.1007/s12652-017-0519-z

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Few decades ago, understanding human behaviors was considered as a mystery where predicting people's future was impossible. Many changes have been noticed since that era. Thanks to current advances in location tracking technology and data mining techniques, predicting users' behaviors has become possible. In this paper we present a new algorithm to online predict users' next visited locations that not only learns incrementally the users' habits, but also detects and supports the drifts in their patterns. Our original contribution includes a new algorithm for online association rules mining that supports the concept drift.

引用

页码：1345 / 1357

页数：13

共 19 条

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