Cognitive agents for understanding the complexities involved in web-based knowledge-gathering tasks

Authors:
Balaji Rajendran;K. Iyakutti
Affiliations:
Madurai Kamaraj University, Madurai, India;Madurai Kamaraj University, Madurai, India
Venue:
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Year:
2009

Citing 11
Cited 0

Recommending and evaluating choices in a virtual community of use

CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Autonomous interface agents

Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
The RETSINA MAS Infrastructure

Autonomous Agents and Multi-Agent Systems
A taxonomy of web search

ACM SIGIR Forum
Organizing encyclopedic knowledge based on the web and its application to question answering

ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
The Knowledge Grid

The Knowledge Grid
Tutorial on agent-based modeling and simulation part 2: how to model with agents

Proceedings of the 38th conference on Winter simulation
A cognitive approach for agent-based personalized recommendation

Knowledge-Based Systems
Web Information Retrieval Support Systems: The Future of Web Search

WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Socio-contextual model of knowledge sharing among userassisting agents

ISI'09 Proceedings of the 2009 IEEE international conference on Intelligence and security informatics
A Survey of Artificial Cognitive Systems: Implications for the Autonomous Development of Mental Capabilities in Computational Agents

IEEE Transactions on Evolutionary Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

A Web-based knowledge-gathering task is a common, but complex activity carried out by several users on the Web. The complexity is of two types: One is the inherent complexity involved in the task, which is essentially the information need of the user, and the other is the perceived complexity by the user-that varies according to the proficiency of the user, in the particular subject matter of the task. We present an Agent-based Cognitive model for understanding both the inherent and perceived complexities. We conducted simulation of our model using logs of user sessions to arrive at the typical complexity values and to qualitatively represent them. We also carried out live experimentation through a prototype system that made estimates of the complexities as users were involved in Kwowledge gathering tasks, and the results vindicated our estimations.