2011 Proceeding
On behalf of the organizing committee, it is our great pleasure to welcome you to the 20th ACM Conference on Information and Knowledge Management in Glasgow!
Since its inception, the CIKM conference has provided a unique international forum for the presentation, discussion and dissemination of research findings in data management, information retrieval and knowledge management. The purpose of the conference is to identify challenging problems facing the development of future knowledge and information systems and to shape future research directions through the publication of high quality, applied and theoretical research findings. The conference has been a leading forum in which experts from academic, industry and the public sector gather to exchange ideas, research achievements and technical developments in multidisciplinary research areas.
CIKM is one of the world's most recognized conferences in the field. This year CIKM received 918 full paper submissions, 220 poster submissions, and 56 demonstration submissions. This is a great demonstration of the lively research areas that contribute to the CIKM area. In addition, CIKM 2011 will host 10 tutorials from leading researchers, 15 workshops on cutting-edge areas of research, a panel session on Social and Collaborative Search and a dedicated Industry Day featuring leading industrial practitioners. We are grateful to all authors who chose to submit their research to CIKM 2011 and are very excited by the final program.
CIKM values interdisciplinary research and we are proud to present three keynote speakers, Professor Justin Zobel, Professor Maurizio Lenzerini and Professor David Karger, all of whom will give presentations that cross discipline boundaries.
Collective prediction with latent graphs
Collective classification in relational data has become an important and active research topic in the last decade. It exploits the dependencies of instances in a network to improve predictions. Related applications include hyperlinked document ...
Who will follow you back?: reciprocal relationship prediction
We study the extent to which the formation of a two-way relationship can be predicted in a dynamic social network. A two-way (called reciprocal) relationship, usually developed from a one-way (parasocial) relationship, represents a more trustful ...
Link prediction: the power of maximal entropy random walk
Link prediction is a fundamental problem in social network analysis. The key technique in unsupervised link prediction is to find an appropriate similarity measure between nodes of a network. A class of wildly used similarity measures are based on ...
Exploiting longer cycles for link prediction in signed networks
We consider the problem of link prediction in signed networks. Such networks arise on the web in a variety of ways when users can implicitly or explicitly tag their relationship with other users as positive or negative. The signed links thus created ...
Structural link analysis and prediction in microblogs
With hundreds of millions of participants, social media services have become commonplace. Unlike a traditional social network service, a microblogging network like Twitter is a hybrid network, combining aspects of both social networks and information ...
Temporal link prediction by integrating content and structure information
In this paper we address the problem of temporal link prediction, i.e., predicting the apparition of new links, in time-evolving networks. This problem appears in applications such as recommender systems, social network analysis or citation analysis. ...
Index Terms
- Proceedings of the 20th ACM international conference on Information and knowledge management