A Grid-based Spatial Association Mining Method

2007 ◽  
Author(s):  
Xiaohui Zhao ◽  
Yu Fang
Keyword(s):  
Spatial Association ◽  
Association Mining ◽  
Mining Method ◽  
Grid Based

scholarly journals Association mining method based on neighborhood perspective

2020 ◽  
Vol 50 (6) ◽  
pp. 824-844
Author(s):  
Honghong CHENG ◽  
Jiye LIANG ◽  
Yuhua QIAN ◽  
Zhiguo HU
Keyword(s):  
Association Mining ◽  
Mining Method

Research and Application of a Multidimensional Association Rules Mining Method Based on OLAP

2021 ◽  
Vol 16 (1) ◽  
pp. 75-94
Author(s):  
Hairong Wang ◽  
Pan Huang ◽  
Xu Chen
Keyword(s):  
Association Rules ◽  
Real Data ◽  
Association Mining ◽  
Mining Method ◽  
Association Rules Mining ◽  
Factors Affecting ◽  
Intermediate Data ◽  
On Line ◽  
Analysis System ◽  
Mining Model

As to the problems of low data mining efficiency, less dimensionality, and low accuracy of traditional multidimensional association rules in the university big data environment, an OLAP-based multi-dimensional association rule mining method is proposed, which combines hash function and marked transaction compression technology to solve the problem of excessive or redundant candidate sets in the Apriori algorithm, and uses On Line Analytical Processing to manage the intermediate data in the association mining process , in order to reduce the time overhead caused by repeated calculations. To verify the validity of the proposed method, a learning situation analysis system is constructed in the field of colleges and universities. The multi-dimensional association rules mining method is used to analyze more than 21,000 desensitized real data, in order to mine the key factors affecting students' academic performance. The experimental results show that the proposed multi-dimensional mining model has good mining results and significantly improves the time performance.

scholarly journals An Innovative Video Summary and Pattern Mining using VSP Algorithm

2019 ◽  
Vol 8 (3S) ◽  
pp. 610-614
Keyword(s):  
Pattern Mining ◽  
Distinct Group ◽  
Video Sequences ◽  
Association Mining ◽  
Frequent Patterns ◽  
Two Dimensional ◽  
Mining Method ◽  
Video Summary ◽  
Mining Algorithm ◽  
Innovative Method

This paper proposes a VSP-TREE algorithm that mines l associations from video. A tool is designed to annotate the Video sequences by giving appropriate values to the sequence and then these values are converted into two-dimensional datasets suitable for clustering. The datasets are clustered using innovative algorithm to form distinct group and known as summary candidate with user size, our system make summary by choosing important frame from candidate cluster and put them in original. A VSP-TREE Based Mining method is used find out frequent patterns occurrence in the video. Association mining algorithm used on clustered datasets with innovative method, Video sequential pattern Tree (VSP Tree) Structure to generate frequent patterns through efficient methodology called conditional search.

scholarly journals Discovering spatial interaction patterns of near repeat crime by spatial association rules mining

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Zhanjun He ◽  
Liufeng Tao ◽  
Zhong Xie ◽  
Chong Xu
Keyword(s):  
Pattern Mining ◽  
Spatial Interaction ◽  
Spatial Association ◽  
Association Mining ◽  
Interaction Patterns ◽  
Spatio Temporal ◽  
Temporal Interaction ◽  
Near Repeat ◽  
Temporal Interactions ◽  
Spatial Transmission

Abstract Urban crime incidents always exhibit a structure of spatio-temporal dependence. Exploration of the spatio-temporal interactions of crime incidents is critical to understanding the occurrence mechanism and spatial transmission characteristics of crime occurrences, therefore facilitating the determination of policing practices. Although previous researches have repeatedly demonstrated that the crime incidents are spatially clustered, the anisotropic characteristics of spatial interaction has not been fully considered and the detailed spatial transmission of crime incidents has rarely been explored. To better understand the spatio-temporal interaction patterns of crime occurrence, this study proposes a new spatial association mining approach to discover significant spatial transmission routes and related high flow regions. First, all near repeat crime pairs are identified based on spatio-temporal proximity. Then, these links between close pairs are simplified by spatial aggregation on spatial grids. Based on that, measures of the spatio-temporal interactions are defined and a spatial association pattern mining approach is developed to discover significant spatial interaction patterns. Finally, the relationship between significant spatial transmission patterns and road network structure is analyzed. The experimental results demonstrate that our approach is able to effectively discover spatial transmission patterns from massive crime incidents data. Our results are expected to provide effective guidance for crime pattern analysis and even crime prevention.

Applied Research of Association Mining Technology in Student Achievement Analysis System

2014 ◽  
Vol 687-691 ◽  
pp. 1580-1583
Author(s):  
Ying Hui Wang
Keyword(s):  
Data Mining ◽  
Student Achievement ◽  
Applied Research ◽  
School Administrators ◽  
Relevant Information ◽  
Association Mining ◽  
Mining Method ◽  
Use Of Data ◽  
Analysis System ◽  
Simple Query

Most colleges and universities have built a database of student achievement, but only a simple query and statistical operations, while hiding behind the data in these achievements even more valuable information has not been excavated and use. To solve this problem, this paper proposes the use of data mining association mining method on student achievement dig deeper; get relevant information between different courses for school administrators in decision analysis, the teacher's lesson plans and student learning arrangements.

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