Dr. Sotirios Chatzis has recently got accepted a FULL paper in one of the most prestigious Data Mining conferences, namely ACM CIKM 2013. A highly selective conference, the acceptance rate of which has never exceeded 16% for full paper submissions.
In his paper entitled "Nonparametric Bayesian Multitask Collaborative Filtering," Dr. Chatzis presents a method that addresses the data sparsity problem collaborative filtering systems suffer from. His method allows for optimally exploiting information from multiple tasks to increase the performance of collaborative filtering systems, by detecting task sets sharing common underlying patterns, and performing targeted information sharing between such tasks.
The presented method yielded state-of-the-art results on two benchmark datasets. This paper of Dr. Chatzis has also been nominated for the best paper award of the conference.
Publication in one of the most prestigious conferences on Data Mining
Dr. Sotirios Chatzis has recently got accepted a FULL paper in one of the most prestigious Data Mining conferences, namely ACM CIKM 2013. A highly selective conference, the acceptance rate of which has never exceeded 16% for full paper submissions.
In his paper entitled "Nonparametric Bayesian Multitask Collaborative Filtering," Dr. Chatzis presents a method that addresses the data sparsity problem collaborative filtering systems suffer from. His method allows for optimally exploiting information from multiple tasks to increase the performance of collaborative filtering systems, by detecting task sets sharing common underlying patterns, and performing targeted information sharing between such tasks.
The presented method yielded state-of-the-art results on two benchmark datasets. This paper of Dr. Chatzis has also been nominated for the best paper award of the conference.
