Scope

The Web has become an indispensable instrument in the daily life for business activities, learning, entertainment, communication, etc. Offer of products and services to Internet users is practically unlimited, nevertheless, this apparent advantage is also a great drawback due to the fact that the Web provides from multiple sources a great quantity of heterogeneous information difficult to handle and interpret. In this context, data mining methods arise as efficient tools for helping users in the recovery of suitable information, products or services from the Web. For that reason, recommender systems have become 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.

Nowadays, social networks are big sources of data, from which valuable information can be extracted by means of datamining algorithms. Social media mining allows us to explore a wide range of aspects regarding users, communities, networks structures, information diffusion and so on.

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

Topics

Topics of interest may include, but are not limited to, the following matters

Web Mining: content, structure and usage mining.
Web Mining Agents.
Opinion mining.
Sentiment analysis.
User profiling and personalization.
Social influence analysis.
Community analysis.
Recommender Systems: Technologies, methodologies and applications.
Context-aware recommender systems.
Recommender Agents.
Semantic Web Technologies for Recommender Systems.
Semantic Web Mining.
Semantic Web Personalization.
Visualization Techniques.