Similarity estimation techniques from rounding algorithms
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
DEXA '06 Proceedings of the 17th International Conference on Database and Expert Systems Applications
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Recently, in Japan, some farming districts established their locality as brands, and prices of agricultural products differs from their grown places. This induced some agricultural food origin forgery cases. Food traceability systems are introduced and some are now in operation to solve this problem. However, food traceability systems have vulnerabilities in their nature because they traces only artificially attached IDs. So there are possibility to forge ID and packages, and switching the vegetables in packages. So, we developed a geographical origin identification system for vegetables by using their trace element compositions. Trace element means very small quantities of elements. This system gathers trace element data of vegetables when shipping from farms, and stores them into databases located in farming districts. In case of a vegetable which has doubtful geographical origin is found in markets, their trace element compositions are measured and compared with data in databases to find its actual geographical origin. Our system judges geographical origin by whether correlation coefficient. This requires calculating correlation coefficients for identifying one and all stored data. However, this is not scalable for the number of data. In this paper, we describe a method to limit the number of data to be used to calculate correlation coefficients before calculating them, and realize scalability.