Information extraction from a large number of micro-sensory data without location attribute

2015 Fiscal Year Final Research Report

• Project/Area Number: 25330099
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Information network
• Research Institution: Chiba University
• Principal Investigator: Shioda Shigeo 千葉大学, 工学(系)研究科(研究院), 教授 (70334167)
• Project Period (FY): 2013-04-01 – 2016-03-31
• Keywords: センサ / 位置推定 / グラフ描画 / オンラインソーシャルネットワーク / ランダムウォーク / 対象物カウント

Outline of Final Research Achievements

Fundamental theories for extracting the meaningful information from a large number of micro-sensory data collected by numerous sensors located in real or virtual world are established, and their applications to various subjects are examined. Particular focus are put on the following subjects: (1) cooperative sensor localization based on inter-sensor distances，(2) cooperative sensor localization based on binary inter-sensor-distance information, (3) graph drawing method parameterized for varying the layout, (4) target object counting using binary proximity sensors via cluster identification，(5) random-walk-based biased sampling for data collection in on-line social networks.

Free Research Field

情報通信