The First International Workshop on
Mining Communities and People Recommenders

Full-day Workshop in conjunction with the IEEE International Conference on Data Mining (ICDM) 2011, Vancouver, Canada

December 11, 2011

Call For Papers (pdf)

Data mining and knowledge discovery in social networks has advanced significantly over the past several years, due to the availability of a large variety of online and online social network systems. The focus of COMMPER is on two main streams of social networks: community mining and system recommenders.

The first focus of this workshop is on mining communities in social networks and in particular in scientific collaboration networks. Consider, for example, a dataset of scientific publications along with information about each publication and the complete citation network. Many data-analysis questions arise: what are the underlying communities, who are the most influential authors, what are the set-skills of individual authors, what are the observed collaboration patterns, how does interest on popular topics propagates, who does the network evolve in terms of collaborations, topics, citations, and so on. In this workshop we indent to bring domain experts, such as bibliometricians, closer to researchers from the fields of data mining and social networks. The expected outcome is to strengthen the collaboration of these communities aiming at high impact-research contributions and discussions. We aspire that the workshop will lead to the development of new insights and data mining methodologies that could be employed for the analysis of communities, models of human collaboration, topic discovery, evolution of social networks, and more.

People recommenders, the second main topic of this workshop, deal with the problem of finding meaningful relationships among people or organisations. In online social networks, relationships can be friends on Facebook, professional contacts on LinkedIn, dates on an online dating site, jobs or workers on employment websites, or people to follow on Twitter. The nature of these domains makes people-to-people recommender systems to be significantly different from traditional item-to-people recommenders. One basic difference in the people recommender domain is the benefit or requirement of reciprocal relationships. Another difference between these domains is that people recommenders are likely to have rich user profiles available. The goal of this workshop is to build a community around people recommenders and instigate discussion about this emerging area of research for recommender systems. With this workshop, we want to reach out to research done in both academia and industry.


We encourage that papers submitted to COMMPER focus on, but are not limited to the following topics:


Camera-ready Submission Information

The camera-ready version of all accepted papers is due on October 14 2011. Note that this is an absolutely *HARD* deadline. To submit your camera-ready please use the ICDM author's kit.

Submission Information

All papers will be assigned to three reviewers for peer review. If accepted, at least one of the authors must attend the Workshop to present the paper; this is a requirement in order for the paper to be included in the IEEE Digital Library.

All papers must be formatted in the IEEE Computer Society proceedings manuscript style. All paper submissions should be limited to a maximum of 8 pages (full papers) and 6 pages (short papers) in the IEEE 2-column format. Please note that up to two additional pages can be purchased at 125 USD per page. Papers that do not comply with the Submission Guidelines will be rejected without review.

For detailed formatting guidelines please visit the IEEE ICDM 2011 website. Papers should be submitted through the ICDM Workshop submission site.

Papers submitted to this workshop must not have been accepted for publication elsewhere or be under review for another workshop, conference, or journal.


Accepted papers will be published in the ICDM Workshops Proceedings.

Workshop Organizers

Program Committee

Invited Speaker

Evimaria Terzi, Assistant Professor, Boston University, USA.

Title: Algorithmic problems in review-management systems

Abstract: As online review-management systems (e.g., Yelp, Amazon and many more) proliferate, there is a need for mechanisms that aim to improve the user experience. In the first part of the talk, we will focus on the users-consumers; the consumers use the reviews in order to make informed decisions for a variety of tasks, ranging from entertainment and shopping to medical services. Thus, their goal is to use the online reviews in order to get a comprehensive view of the product they are interested in. Here, we will present a general framework that allows for the selection of a small set of high-quality reviews to be shown to the customers so that they get information about many different aspects of the reviewed item. In the second part of the talk, we will focus on the users-reviewers; the reviewers use the online review systems as a means to have their opinions heard by by the largest possible number of people. Here, we will present a framework that aims towards keeping the reviewers satisfied and motivated to continue submitting high-quality content. In both parts of the talk, we will focus on the algorithmic problems as well as the practical challenges that arise when applying our algorithms in real-world review management systems.




COMMPER 2011 — The First International Workshop on Mining Communities and People Recommenders, 2011