Naoto Ohsaka

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Influence maximization is a problem to find small sets of highly influential individuals in a social network to maximize the spread of influence under stochastic cascade models of propagation. Although the problem has been well-studied, it is still highly challenging to find solutions of high quality in large-scale networks of the day. While(More)
We propose the first real-time fully-dynamic index data structure designed for influence analysis on evolving networks. With this aim, we carefully redesign the data structure of the state-of-the-art sketching method introduced by Borgs et al., and construct corresponding update algorithms. Using this index, we present algorithms for two kinds of queries,(More)
Real-world networks, such as the World Wide Web and online social networks, are <i>very large</i> and are <i>evolving rapidly</i>. Thus tracking personalized PageRank in such evolving networks is an important challenge in network analysis and graph mining. In this paper, we propose an efficient online algorithm for tracking personalized PageRank in an(More)
When most of the K+ in a chemically defined medium was replaced with Rb+, cell growth of HeLa cells was strongly inhibited. The growth was partially but significantly restored by an addition of 5% dialyzed calf serum to the medium. The inhibition of cell growth in Rb+-substituted medium was partly due to suppression of protein synthesis by K+ deficiency,(More)
This article proposes a reinforcement learning method aimed at improving the sweeping efficiency of an agent. In the proposed method, an agent attempts to avoid overlapping a swept field by using a combination of distances from the agent to obstacles and the information which expresses whether a field in front of the agent has already been swept. We carried(More)
Motivated by viral marketing, stochastic diffusion processes that model influence spread on a network have been studied intensively. The primary interest in such models has been to find a seed set of a fixed size that maximizes the expected size of the cascade from it. Practically, however, it is not desirable to have the risk of ending with a small(More)