著者

横林 亮平

出版者

法政大学大学院理工学研究科

雑誌

法政大学大学院紀要. 理工学・工学研究科編 (ISSN:21879923)

巻号頁・発行日

no.60, pp.1-8, 2019-03-31

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The tensor data model is capable of detailed data representation and is compatible with data mining. However, there is a problem that the data volume becomes enormous and processing time is required. It is one solution to this problem to improve the efficiency of a series of data processing such as insertion, deletion, search of data in the secondary storage area. In this paper, we propose an serial search method using locality sensitive hashing. The hash technique is a search method that is hardly affected by the data amount, but there is a problem that the serial search can not be performed. By using locality sensitive hashing, we sequentially arrange similar data in the same block and improve efficiency by carrying out parallel processing for each block. We will also describe the efficiency of tensor data manipulation (especially data mining manipulation). Using locality sensitive hashing, realize high-speed multidimensional association rules extraction limited to partial data.