An Efficient Association Mining Method via Matrix Compression

2016 ◽  
Author(s):  
Yurong Zhong ◽  
Dan Liu
Keyword(s):  
Association Mining ◽  
Mining Method ◽  
Matrix Compression

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.

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.

Similarity Detection Using Latent Semantic Analysis Algorithm

2018 ◽  
Vol 6 (8) ◽  
pp. 102
Author(s):  
Priyanka R. Patil ◽  
Shital A. Patil
Keyword(s):  
Latent Semantic Analysis ◽  
Latent Dirichlet Allocation ◽  
Semantic Analysis ◽  
Mining Method ◽  
Research Papers ◽  
Information Measures ◽  
Automated Software ◽  
Day By Day ◽  
Ways Of Life ◽  
Dirichlet Allocation

Similarity View is an application for visually comparing and exploring multiple models of text and collection of document. Friendbook finds ways of life of clients from client driven sensor information, measures the closeness of ways of life amongst clients, and prescribes companions to clients if their ways of life have high likeness. Roused by demonstrate a clients day by day life as life records, from their ways of life are separated by utilizing the Latent Dirichlet Allocation Algorithm. Manual techniques can't be utilized for checking research papers, as the doled out commentator may have lacking learning in the exploration disciplines. For different subjective views, causing possible misinterpretations. An urgent need for an effective and feasible approach to check the submitted research papers with support of automated software. A method like text mining method come to solve the problem of automatically checking the research papers semantically. The proposed method to finding the proper similarity of text from the collection of documents by using Latent Dirichlet Allocation (LDA) algorithm and Latent Semantic Analysis (LSA) with synonym algorithm which is used to find synonyms of text index wise by using the English wordnet dictionary, another algorithm is LSA without synonym used to find the similarity of text based on index. LSA with synonym rate of accuracy is greater when the synonym are consider for matching.

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