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Advances in Artificial Intelligence
Volume 2012 (2012), Article ID 562604, 18 pages
http://dx.doi.org/10.1155/2012/562604
Research Article

A Method for Identifying Japanese Shop and Company Names by Spatiotemporal Cleaning of Eccentrically Located Frequently Appearing Words

1Center for Spatial Information Science, The University of Tokyo, Cw-503 Shibasaki Laboratory, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
2Center for Spatial Information Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa City, Chiba 277-8568, Japan

Received 23 July 2011; Revised 9 November 2011; Accepted 2 December 2011

Academic Editor: Mohamed Afify

Copyright © 2012 Yuki Akiyama and Ryosuke Shibasaki. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

We have developed a method for spatiotemporally integrating databases of shop and company information, such as from a digital telephone directory, spatiotemporally, in order to monitor dynamic urban transformations in a detailed manner. To realize this, an additional method is necessary to verify the identicalness of different instances of Japanese shop and company names that might contain fluctuations of description. In this paper, we discuss a method that utilizes an -gram model for comparing and identifying Japanese words. The processing accuracy was improved through developing various kinds of libraries for frequently appearing words, and using these libraries to clean shop and company names. In addition, the accuracy was greatly and novelty improved through the detection of those frequently appearing words that appear eccentrically across both space and time. By utilizing natural language processing (NLP), our method incorporates a novel technique for the advanced processing of spatial and temporal data.