SCOPE

Recommender systems are becoming very popular in recent years, mainly in the e-commerce sites, although they are increasing in importance in other areas such as e-learning, tourism, news pages, etc. These systems are endowed with intelligent mechanisms to personalize recommendations about products or services. Data mining techniques are efficient methods for personalized selective retrieval of web information. The process of applying data mining techniques on web data is known as web mining.

Web mining tasks can be carried out automatically by means of software agents. The use of agents in web applications is widely extended, mainly in search engines and e-commerce environments, where they play diverse roles. Their autonomy, learning capability and the possibility of working in cooperation with other agents are suitable properties for their use in the personalization of web systems by means of data mining techniques.

WebMiReS aims at providing a forum for the presentation and discussion of the advances achieved in the web mining field.

TOPICS

Web Usage Mining
Web Content Mining
Web Structure Mining
Web Mining Agents
Recommender Systems’ Technologies and Methodologies
User Profiles
Preference Prediction
Recommender Agents
Fuzzy Methods
Hybrid Techniques
Semantic Web Technologies for Recommender System
Semantic Web Mining
Semantic Web Personalization
Context-aware Recommender Systems
Visualization Techniques
Applications: e-Commerce, e-Learning, Tourism Web Systems, Digital Libraries…