Special Issue on: "Mining Social Networks for Recommender Systems"
Dr. Panagiotis Symeonidis and Prof. Dr. Yannis Manolopoulos, Aristotle University, Greece
Social networks such as Facebook, Linkedin, etc. contain gigabytes of data that can be mined to make recommendations for products, events or even friendships. The premise of these recommendations is that individuals might only be a few steps from a desirable social friend, event or product, but not realise it.
In such systems, people often belong to multiple explicit or implicit social networks because of different interpersonal interactions. That is, besides the explicit friendship relations between the users, there are also other implicit relations. For example, users can co-comment on products and they can co-rate products or co-tag a photo.
The aim of this special issue is to study how mining of social networks can leverage the quality of recommendations. The analysis of social influence and the inference of social rating networks and social media can help in providing more accurate and effective product, friend, activity and event recommendations.
Suitable topics include but are not limited to:
- Link prediction in social networks
- Rating prediction in social rating networks
- Recommendation in social rating networks
- Cross-domain recommendation in social rating networks
- Group recommendation in social networks
- Top-N friend recommendation in social networks
- Top-N item recommendation in social networks
- Recommendation in social networks with distrust
- Recommendation in time-evolving social networks
- Social network analysis for recommendation
- Memory-based methods for recommendation in social networks
- Model-based methods for recommendation in social networks
- Recommendation by combining multiple social networks
- Privacy of recommendation in social networks
- Event and activity recommendation in mobile social networks
- Recommendation in location-based social networks
- Collaborative filtering in social networks
- Context-aware recommendation in social networks
- Explaining recommendation in social networks
- Recommendation in social media
- Multi-criteria recommendation in social networks
Notes for Prospective Authors
Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper was not originally copyrighted and if it has been completely re-written).
All papers are refereed through a peer review process. A guide for authors, sample copies and other relevant information for submitting papers are available on the Author Guidelines page.
Paper submission due: 1 February, 2013
First round notification: 1 May, 2013
Revised version due: 1 August, 2013
Editors and Notes
All papers must be submitted online. To submit a paper, please read our information on preparing and submitting articles. If you experience any problems submitting your paper online, please contact email@example.com, describing the exact problem you experience. Please include in your submission the title of the Special Issue, the title of the Journal and the names of the Guest Editors