Web User Interact Task Recognition Based on Conditional Random Fields

被引：4

作者：

Elbahi, Anis ^{[1
]}

Omri, Mohamed Nazih ^{[1
]}

机构：

[1] Fac Sci Monastir, Dept Comp Sci, Res Unit MARS, Monastir, Tunisia

来源：

COMPUTER ANALYSIS OF IMAGES AND PATTERNS, CAIP 2015, PT I | 2015年 / 9256卷

关键词：

Conditional random fields; Hidden markov models; User task recognition; Cursor behavior analysis; Human computer interaction; Pattern recognition; Machine learning;

D O I：

10.1007/978-3-319-23192-1_62

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Recognition activity of web users based on their navigational behavior during interaction process is an important topic of Human Computer Interaction. To improve the interaction process and interface usability, many studies have been performed for understanding how users interact with a web interface in order to perform a given activity. In this paper we apply the Conditional Random Fields approach for modeling human navigational behavior based on mouse movements to recognize web user tasks. Experimental results show the efficiency of the proposed model and confirm the superiority of Conditional Random Fields approach with respect to the Hidden Markov Models approach in human activity recognition.

引用

页码：740 / 751

页数：12

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