Welcome to Social Web Mining Workshop, co-located with IJCAI 2011

Social Web Mining Workshop, co-located with IJCAI 2011

International Workshop on Social Web Mining

Co-located with IJCAI, 18 July 2011, Barcelona, Spain

Sponsored by PASCAL 2

News: the submission deadline has been extended to 20 April 2011.

Introduction:

There is increasing interest in social web mining, as we can see from the ACM workshop on Social Web Search and Analysis. It is not until recently that great progresses have been made in mining social network for various applications, e.g., making personalized recommendations. This workshop focuses on the study of diverse aspects of social networks with their applications in domains including mobile recommendations, service providers, electronic commerce, etc.

Social networks have actually played an important role in different domains for about a decade, particularly in recommender systems. In general, traditional collaborative filtering approaches can be considered as making personalized recommendations based on implicit social interaction, where social connections are defined by some similarity metrics on common rated items, e.g., movies for the Netflix Prize.

With the recent development of Web 2.0, there emerges a number of globally deployed applications for explicit social interactions, such as Facebook, Flickr, LinkedIn, Twitter, etc. These applications have been exploited by academic institutions and industries to build modern recommender systems based on social networks, e.g., Microsoft's Project Emporia that recommends tweets to user based on their behaviors.

In recent years, rapid progress has been made in the study of social networks for diverse applications. For instance, researchers have proposed various tensor factorization techniques to analyze user-item-tag data in Flickr for group recommendations. Also, researchers study Facebook to infer users' preferences.

However, there exist many challenges in mining social web and its application in recommender systems. Some are:

• What is the topology of social networks for some specific application like LinkedIn?
• How could one build optimal models for social networks such as Facebook?
• How can one handle the privacy issue caused by utilizing social interactions for making recommendation?
• How could one model a user's preferences based on his/her social interactions?

We hope to gather scientific researchers and industry in order to discuss the challenges, exchange ideas, and promote collaborations across different groups.

Topics:

The workshop will seek submissions that cover social networks, data mining, machine learning, and recommender systems. The workshop is especially interested in papers that focus on applied domains such as web mining, mobile recommender systems, social recommender systems, and privacy in social web mining. The following list provides examples of the types of areas in which we encourage submissions. The following comprises a sample, but not complete, listing of topics:

• Active learning
• Matchmaking
• Mobile recommender systems
• Multi-task learning
• Learning graph matching
• Learning to rank
• Online and contextual advertising
• Online learning
• Privacy in social networks
• Preference learning or elicitation
• Social network mining
• Social summarization
• Tag recommendation
• Transfer learning
• Web graph analysis