A New Method for Mining Co-location Patterns Between Network Spatial Phenomena

The mining of co-location patterns is a hot issue in the field of spatial data mining.Howev-er,a little attention has been paid to the co-location patterns between network spatial phenomena.This paper extends an existing approach to mining the co-location patterns between network spatialphenomena.The approach consists of two core stages:①ｄｅｆｉｎｉｎｇ　ａ　ｃｏ－ｌｏｃａｔｉｏｎ　ｍｏｄｅｌ　ｔｏ　ｈａｖｅ　ｃｏ－ｏｃ－ｃｕｒｒｅｎｃｅ　ｒｅｌａｔｉｏｎｓ　ｂｙ　ｐａｒｔｉｔｉｏｎｉｎｇ　ｔｈｅ　ｎｅｔｗｏｒｋ；②ｃｏｍｐｕｔｉｎｇ　ｔｈｅ　ｓｔａｔｉｓｔｉｃａｌ　ｄｉａｇｎｏｓｔｉｃｓ　ｆｏｒ　ｔｈｅｓｅ　ｃｏ－ｏｃ－ｃｕｒｒｅｎｃｅ　ｒｅｌａｔｉｏｎｓ．Ｔｈｅ　ａｐｐｒｏａｃｈ　ｈａｓ　ｂｅｅｎ　ａｐｐｌｉｅｄ　ｔｏ　ａ　ｃａｓｅ　ｓｔｕｄｙ，ｗｈｉｃｈ　ｄｅａｌｔ　ｗｉｔｈ　ｔｈｅ　ｍｉｎｉｎｇ　ｏｆ　ｔｈｅｃｏ－ｌｏｃａｔｉｏｎ　ｐａｔｔｅｒｎｓ　ｏｆ　ｍａｎｕｆａｃｔｕｒｉｎｇ　ｆｉｒｍｓ　ｉｎ　Ｓｈｅｎｚｈｅｎ　Ｃｉｔｙ，Ｃｈｉｎａ．Ｔｈｅ　ｃｏ－ｌｏｃａｔｉｏｎ　ｐａｔｔｅｒｎｓ　ｈａｖｅｂｅｅｎ　ａｎａｌｙｚｅｄ　ｑｕａｌｉｔａｔｉｖｅｌｙ　ａｃｃｏｒｄｉｎｇ　ｔｏ　ｔｈｅ　ｔｈｒｅｅ　ｍｅｃｈａｎｉｓｍｓ　ｄｅｒｉｖｅｄ　ｆｒｏｍ　ａｇｇｌｏｍｅｒａｔｉｏｎ　ｅｃｏｎｏｍｉｃｓ．Ｔｈｅ　ｖａｌｉｄａｔｉｏｎ　ｏｆ　ｔｈｅ　ａｐｐｒｏａｃｈ　ｈａｓ　ｂｅｅｎ　ｖｅｒｉｆｉｅｄ　ｂｙ　ｔｈｅ　ｃｏｍｐａｒｉｓｏｎ　ｗｉｔｈ　ｔｈｅ　ｅｘｉｓｔｉｎｇ　ｍｅｔｈｏｄ　ａｎｄ　ｔｈｅｎｅｔｗｏｒｋ　ｃｒｏｓｓ　Ｋ－ｆｕｎｃｔｉｏｎ．