著者

小池 聡 島村 博 森川 博之 Satoshi Koike Hiroshi Shimamura Hiroyuki Morikawa

出版者

人工知能学会 ; 2014-

雑誌

人工知能 = journal of the Japanese Society for Artificial Intelligence (ISSN:21882266)

巻号頁・発行日

vol.30, no.2, pp.193-198, 2015-03-01

著者

Nobuharu Kami Teruyuki Baba Satoshi Ikeda Takashi Yoshikawa Hiroyuki Morikawa

出版者

一般社団法人 情報処理学会

雑誌

Journal of Information Processing (ISSN:18826652)

巻号頁・発行日

vol.20, no.3, pp.757-766, 2012 (Released:2012-07-15)

参考文献数

19

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We present a fast algorithm for probabilistically extracting significant locations from raw GPS data based on data point density. Extracting significant locations from raw GPS data is the first essential step of algorithms designed for location-aware applications. Most current algorithms compare spatial/temporal variables with given fixed thresholds to extract significant locations. However, the appropriate threshold values are not clearly known in priori, and algorithms with fixed thresholds are inherently error-prone, especially under high noise levels. Moreover, they do not often scale in response to increase in system size since direct distance computation is required. We developed a fast algorithm for selective data point sampling around significant locations based on density information by constructing random histograms using locality-sensitive hashing. Theoretical analysis and evaluations show that significant locations are accurately detected with a loose parameter setting even under high noise levels.

著者

Sanghyun Kim Hiroyuki Morikawa Reiko Mitsuya Takashi Kawai Jukka Häkkinen

出版者

一般社団法人 日本人間工学会

雑誌

人間工学 (ISSN:05494974)

巻号頁・発行日

vol.49, no.Supplement, pp.S424-S427, 2013-06-01 (Released:2013-07-19)