Personalised Information Gathering and Recommender Systems: Techniques and Trends

• Main Authors: Xiaohui Tao, Xujuan Zhou, Cher Han Lau, Yuefeng Li
• Format: Article
• Language: English
• Published: European Alliance for Innovation (EAI) 2013-02-01
• Series: EAI Endorsed Transactions on Scalable Information Systems
• Subjects: Personalisation; Information Gathering; Recommender Systems
• Online Access: http://eudl.eu/doi/10.4108/trans.sis.2013.01-03.e4

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.