Personalised information gathering and recommender systems : techniques and trends


Autoria(s): Tao, Xiaohui; Zhou, Xujuan; Lau, Cher Han; Li, Yuefeng
Data(s)

2013

Resumo

With the explosive growth of resources available through the Internet, information mismatching and overload have become a severe concern to users. Web users are commonly overwhelmed by huge volume of information and are faced with the challenge of finding the most relevant and reliable information in a timely manner. Personalised information gathering and recommender systems represent state-of-the-art tools for efficient selection of the most relevant and reliable information resources, and the interest in such systems has increased dramatically over the last few years. However, web personalization has not yet been well-exploited; difficulties arise while selecting resources through recommender systems from a technological and social perspective. Aiming to promote high quality research in order to overcome these challenges, this paper provides a comprehensive survey on the recent work and achievements in the areas of personalised web information gathering and recommender systems. The report covers concept-based techniques exploited in personalised information gathering and recommender systems.

Identificador

http://eprints.qut.edu.au/59432/

Publicador

Institute of Electronics, Information and Communication Engineers

Relação

DOI:10.4108/trans.sis.2013.01-03.e4

Tao, Xiaohui, Zhou, Xujuan, Lau, Cher Han, & Li, Yuefeng (2013) Personalised information gathering and recommender systems : techniques and trends. IEICE Transactions on Information and Systems, 13(1-3), e4.

Direitos

Copyright 2013 Tao et al.,

licensed to ICST. This is an open access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/trans.sis.2013.01-03.e4

Fonte

School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #080107 Natural Language Processing #080109 Pattern Recognition and Data Mining #080199 Artificial Intelligence and Image Processing not elsewhere classified #080704 Information Retrieval and Web Search #personalisation #information gathering #recommender systems
Tipo

Journal Article