Authors:
Karim Sehaba
1
and
Benoît Encelle
2
Affiliations:
1
Université de Lyon, CNRS, Université de Lyon 2, LIRIS, UMR5205 and France
;
2
Université de Lyon, CNRS, Université de Lyon 1, LIRIS, UMR5205 and France
Keyword(s):
Knowledge Extraction, Interaction Traces, Task Model, ConcurTaskTrees (CTT), Web Browsing Assistance.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Communication, Collaboration and Information Sharing
;
Intelligent Information Systems
;
Knowledge Management and Information Sharing
;
Knowledge Management Projects
;
Knowledge-Based Systems
;
Symbolic Systems
;
Tools and Technology for Knowledge Management
Abstract:
This work focuses on the extraction of knowledge from observed usage. More specifically, it aims to design a Web browsing assistance system that helps the user in carrying out his browsing task, or the designer in adapting or redesigning his Web application, according to real usage. The proposed approach consists of generating task models from interaction traces, which are then used to perform assistance. The characteristics to be supported by a task metamodel for assistance purposes are first identified and then confronted with the characteristics of existing task metamodels. This first study led us to choose the ConcurTaskTrees (CTT) metamodel. We then developed processes to generate CTT task models from traces. Finally, to validate our approach, we conducted unit testing and validation based on two real web browsing scenarios.