5 citations · 10 across the 4 of their papers we have counts for
4 papers
Structured Inverted-File k-Means Clustering for High-Dimensional Sparse Data
Kazuo Aoyama, Kazumi Saito
This paper presents an architecture-friendly k-means clustering algorithm called SIVF for a large-scale and high-dimensional sparse data set. Algorithm efficiency on time is often…
Inverted-File k-Means Clustering: Performance Analysis
Kazuo Aoyama, Kazumi Saito, Tetsuo Ikeda
This paper presents an inverted-file k-means clustering algorithm (IVF) suitable for a large-scale sparse data set with potentially numerous classes. Given such a data set, IVF eff…
Learning Asynchronous-Time Information Diffusion Models and its Application to Behavioral Data Analysis over Social Networks
Kazumi Saito, Masahiro Kimura, Kouzou Ohara +1
One of the interesting and important problems of information diffusion over a large social network is to identify an appropriate model from a limited amount of diffusion informatio…
Efficient Detection of Hot Span in Information Diffusion from Observation
Kouzou Ohara, Kazumi Saito, Masahiro Kimura +1
We addressed the problem of detecting the change in behavior of information diffusion from a small amount of observation data, where the behavior changes were assumed to be effecti…