Application of improved time series Apriori algorithm by frequent itemsets in association rule data mining based on temporal constraint

Wang, Chunxia; Zheng, Xiaoyue

doi:10.1007/s12065-019-00234-5

Cited by 55 publications

(30 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It has been successfully used in computer network, recommendation system, and medical care [9][10]. Wang et al (2020) studied an improved Apriori algorithm for time series of frequent itemsets, applied it to mining association rules based on time constraints, and concluded that this algorithm was superior to the traditional algorithm in storage space [11]. Sun et al (2020) built 0-1 transaction matrix by scanning transaction database to gain weighted support and confidence.…”

Section: Introductionmentioning

confidence: 99%

Sustainable Development of College and University Education by use of Data Mining Methods

Wang

Chung

2021

Int. J. Emerg. Technol. Learn.

View full text Add to dashboard Cite

To improve the education efficiency of the students, the student-centered education plan is explored. First, the Apriori algorithm of association rules is used to mine the potential related patterns in the score data of college students and establish a reasonable teaching method. Second, aided by the decision tree model, the factors affecting students' academic performance are studied, and the potential relationship between different courses is studied. Finally, the Apriori algorithm of association rules combined with decision tree model is used to generate the early warning mechanism of students' achievement, and the course performance of college students is empirically analyzed. The results show that: C language has two sides of dependence on many subjects; higher mathematics → linear algebra → mathematical statistics → computer composition principle → computer network. The teaching scheme of C language → C + + → Java more conforms to the learning mechanism of college students. Through empirical analysis, the early warning mechanism of association rule Apriori algorithm and decision tree model can effectively analyze student's course and give student's achievement. It is found that the method proposed can provide theoretical basis for students, teachers, and university administrators to carry out education reform and education management decision-making, improve students' performance and education quality, and realize the "student-oriented" education concept, so it can be applied to the actual education management.

show abstract

Section: Introductionmentioning

confidence: 99%

Sustainable Development of College and University Education by use of Data Mining Methods

Wang

Chung

2021

Int. J. Emerg. Technol. Learn.

View full text Add to dashboard Cite

show abstract

“…The main idea of deep page Association prefetch is to not only consider the current request of customers, but also consider the current request sequence of customers or the suffix sub-sequence of the current request sequence of customers, so as to improve the accuracy of prefetch [21][22][23]. The basic idea of prefetch model is to use the historical access sequence of customers to build a deep structure tree.…”

Section: Deep Page Association Prefetch Modelmentioning

confidence: 99%

Design and Analysis of Low Delay Deterministic Network Based on Data Mining Association Analysis

Gong

2021

JWE

View full text Add to dashboard Cite

The purpose of this paper is to research on the design and analysis of low delay deterministic network based on data mining association. This paper studies and implements the algorithm of mining page association rules. A session recognition algorithm based on log reference page and request time is proposed by using the time probability relationship of continuous requests. This method improves the accuracy of log data preprocessing and page association rules mining. This paper studies and tests the efficiency, prefetch timing and cache organization of the two page association rules. The results show that in this prefetch scheme, the prefetch performance of the association rules of unordered pages is better than that of the association rules of ordered pages. The prefetch performance when cache hits is better than that when cache fails and the cache fails to hit has better performance. In the case of a certain size of cache space, reasonable organization of cache space can further improve the cache hit rate and reduce the network delay.

show abstract

“…1. Some methods make use of with specific data structures [33][35] [45]. For example, one of the most popular of these methods is the use of hashing function and a file with direct access to store items k > 1 in buckets where the amount of support is calculated based on buckets rather the individual data.Hence, access becomes easy to frequent patterns [29].…”

Section: Related Workmentioning

confidence: 99%

Using BTA Algorithm for Finding Nash Equilibrium Problem Aiming the Extraction of Rules in Rule Learning

Boudaghi

Mahan

Isazadeh

2021

Preprint

View full text Add to dashboard Cite

It is crystal clear that discovering the rules for finding a specific pattern among given data for extraction of association rules and rule-based learning systems has been defined. There is much research that make use of game theory for the processes contributing to discovery of rules. In recent years, modeling based on game theory in rule learning sphere has gained much more attention by computer scientists. When there is independence between the strategies used by two or more different players the strategy game modeling could be used. In this view, strategic play is a desirable model for situations with no permanent strategic relationship among interactions. In addition, Nash equilibrium is the most widely used solution concept in game theory. This concept is a state-of-the-art interpretation of a strategy game. Each player has an accurate prediction of other players' behavior and acts according to such a rational prediction. In the present study, by extracting rules from frequent patterns we have presented a model that can extract learning rules by abstraction based on game theory, which can be used not only for association rules but also for rule-based learning systems. Also, the introduced method can be easily generalized to fuzzy data. To Find Nash Equilibrium (FNE) in the proposed method, we used meta-heuristic Bus Transportation Algorithm (BTA).The results indicated that the method reduces computational complexity in the associate rule discovery process and rule learning, provided that FNE is solved.

show abstract

Application of improved time series Apriori algorithm by frequent itemsets in association rule data mining based on temporal constraint

Cited by 55 publications

References 6 publications

Sustainable Development of College and University Education by use of Data Mining Methods

Sustainable Development of College and University Education by use of Data Mining Methods

Design and Analysis of Low Delay Deterministic Network Based on Data Mining Association Analysis

Using BTA Algorithm for Finding Nash Equilibrium Problem Aiming the Extraction of Rules in Rule Learning

Contact Info

Product

Resources

About