CAJ | 학술논문

高维大数据的相似性计算是数据挖掘领域的研究重点，论文通过分析高维大数据相似性计算的难点，提出采用可拓学的方法解决其中矛盾问题的研究思路。在基元表示高维大数据的基础上，借助数据转换、数据筛选、权重的确定、数据预处理等技术实现了数据之间的相似性计算，并基于水污染常规分析数据进行了算法验证。论文借助可拓的思想研究大数据相似性的问题，不仅对数据挖掘的研究有一定的理论促进，同时也为可拓学的研究提供了新的应用空间。
고유대수거적상사성계산시수거알굴영역적연구중점，논문통과분석고유대수거상사성계산적난점，제출채용가탁학적방법해결기중모순문제적연구사로。재기원표시고유대수거적기출상，차조수거전환、수거사선、권중적학정、수거예처리등기술실현료수거지간적상사성계산，병기우수오염상규분석수거진행료산법험증。논문차조가탁적사상연구대수거상사성적문제，불부대수거알굴적연구유일정적이론촉진，동시야위가탁학적연구제공료신적응용공간。
The similarity calculation of high dimensional big data is a research focus in the field of data mining. In this paper, after analyzing the difficulty of similarity calculation of high dimensional data, a method based on extenics is put forward to solve the contradictory problems.Firstly, the element is used to represent high dimen-sional data.Then the similarity between data is calculated by means of data conversion, data selection, weight determination and data pre-processing technology.Finally the conventional analysis data of water pollution is used to verify the method.The idea of using extenics to solve similarity problem of big data can not only promote theoretical research of data mining, but also provide a new application for extenics.