Guest editorial: Special section on the international conference on data engineering

Christian S. Jensen, Christopher Jermaine, Xiaofang Zhou
2015 IEEE Transactions on Knowledge and Data Engineering  
attracted 443 submissions in the research track, 20 submissions in the industrial track, and 69 demo proposals. Each submission was assigned to three reviewers. The evaluation process had several phases: assignment of papers to reviewers, reviewing, discussions among reviewers, decision making by area chairs, consolidation of decisions, and handling of papers assigned for shepherding. As a result of these efforts, 95 research papers, eight industrial papers, and 27 demos were selected for
more » ... ion in the conference program. This special section consists of journal versions of seven outstanding papers selected among the 95 accepted research papers. All papers were revised and substantially extended over their conference versions and went through a rigorous review process to ensure that the high quality standards of the IEEE Transactions on Knowledge and Data Engineering were met. The seven papers cover a broad range of topics that attest to the scope of ongoing research in data engineering. The paper "Breaking the Barrier to Transferring Link Information across Networks" by Guo-Jun Qi, Charu Aggarwal, and Thomas S. Huang proposes a transfer learning based method for cross-network link prediction. This link prediction model can transfer linkage information from a "mature" source social network to a "young" target network by a bias-correction sampling technique. The paper "Main-Memory Hash Joins on Modern Processor Architectures" by Cagri Balkesan, Jens Teubner, Gustavo Alonso, and M. Tamer Ozsu compares hardwareconscious and hardware-oblivious hash join approaches in empirical studies that consider a large number of workloads and configurations. They find that hardwareconscious algorithms generally outperform hardwareoblivious algorithms, although hardware-oblivious algorithms are competitive under certain circumstances that involve aggressive simultaneous multi-threading.
doi:10.1109/tkde.2015.2419315 fatcat:qawhyhaw4vavvjlvpetxbborui