Computer Science ›› 2018, Vol. 45 ›› Issue (6A): 482-486.

• Big Date & Date Mining • Previous Articles     Next Articles

Co-location Pattern Mining Algorithm Based on Data Normalization

ZENG Xin,LI Xiao-wei,YANG Jian   

  1. College of Mathematics and Computer,Dali University,Dali,Yunnan 671003,China
  • Online:2018-06-20 Published:2018-08-03

Abstract: In the practical application,the spatial features not only contain the spatial information,but also the attribute information,which is important for the knowledge discovery and scientific decision.Existing co-location pattern mining algorithms do not consider the weight of instances of different attributes in the adjacent distance when calculating the adjacent distance of two different feature instances.It results in that the weight of partial attribute is too large and also affects the result of the co-location pattern mining.Standardizing the attribute values and giving an equal weight to all attributes,a data standardization algorithm DNRA based on join-based was put forward.Meanwhile,a deep research was given on the problem that the distance threshold was difficult to determine.The range of the distance threshold was derived in DNRA algorithm,helping the users to select the appropriate distance threshold.Finally,the performance of the DNRA algorithm was analyzed and compared by a large number of experiments.

Key words: Attribute weight, Co-location pattern, Data standardization, Distance threshold

CLC Number: 

  • TP311.13
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