Hideaki Takeda's Publication
- M. Hamasaki and H. Takeda: Neighborhood
Matchmaker Method: A Decentralized Optimization Algorithm for Personal Human
Network, in Proceedings of Seventh International Conference on
Knowledge-Based Intelligent Information & Engineering Systems
(KES2003), pp. 929–935 (2003).
(Paper)
In this paper, we propose an algorithm called Neighborhood
Matchmaker Method to optimize personal human networks. Personal human network
is useful for various utilization of information like information gathering,
but it is usually formed locally and often independently. In order to adapt
various needs for information utilization, it is necessary to extend and
optimize it. Using the neighborhood matchmaker method, we can increase a new
friend who is expected to share interests via all own neighborhoods on the
personal human network. Iteration of matchmaking is used to optimize personal
human networks. We simulate the neighborhood matchmaker method with the
practical data and the random data and compare the results by our method with
those by the central server model. The neighborhood matchmaker method can
reach almost the same results obtained by the sever model with each type of
data.
Hideaki Takeda (National Institute of Informatics)