Hiroyuki Kitagawa

TL;DR: Results obtained from experiments using real-world datasets show that the CARNMF can detect communities and attribute-value clusters more accurately than existing comparable methods, and clustering results obtained using the CAR NMF indicate that CARNMf can successfully detect informative communities with meaningful semantic descriptions through correlations between communities and attributive clusters.

TL;DR: This work not only accelerates the computation of original canopy clustering, but also proposes an algorithm using grid index that partitions the data into cells to reduce redundant computations and, at the same time, to exploit the parallelism of GPUs.

TL;DR: This paper proposes a method called LocalRank to rank web pages by integrating the web and a user database containing information on a specific geographical area using a linked graph structure using entries contained in the database.

TL;DR: The main idea of the optimization is to reduce the writing costs of DBMSs by sharing common store-operators and creates feasible processing plans for multiple persistency requirements.