Learning user interests for user profiling in personal information agents: Thesis

Authors:
Daniela Godoy
Affiliations:
ISISTAN Res. Inst., Univ. Nacional del Centro de la Prov. de Bs. As., Campus Universitario, CP 7000, Tandil, Bs. As., Argentina and CONICET, Consejo Nacional de Investigaciones Científicas y ...
Venue:
AI Communications
Year:
2006

Citing 6
Cited 0

Information agent technology for the Internet: a survey

Data & Knowledge Engineering - Special issue on heterogeneous information resources need semantic access
Enriching Information Agents' Knowledge by Ontology Comparison: A Case Study

IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
User Profiling for Web Page Filtering

IEEE Internet Computing
User profiling in personal information agents: a survey

The Knowledge Engineering Review
Modeling user interests by conceptual clustering

Information Systems - Special issue: The semantic web and web services
Interface agents personalizing Web-based tasks

Cognitive Systems Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

This work presents a novel user profiling technique, named WebProfiler, developed to support incremental learning and adaptation of user profiles for agents assisting users with information-related tasks. This technique aims at acquiring comprehensible user profiles that accurately capture user interests starting from the observation of user behavior on the Web.