An Association Rule-Based Multiresource Mining Method for MOOC Teaching

Jia, Nan; Madina, Zamira

doi:10.1155/2022/6503402

Cited by 5 publications

(6 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Four association rules discovered with their evaluation measures values are shown in Table 10. The first rule discovered shows that based on Lift and Conviction values among the patient records under consideration, women who were in third stage tumor of breast cancer(5), negative HER2 status (12) and have undergone Modified Radical Mastectomy (15) are strongly correlated with Infiltrating Ductal Carcinoma (6) type of cancer and alive post surgery (9). Similarly, second rule shows that women who were in third stage tumor of breast cancer(5) and negative HER2 status ( 12) are strongly correlated with Infiltrating Ductal Carcinoma (6) type of cancer and alive post surgery (9).…”

Section: A Dataset Collectionmentioning

confidence: 99%

See 1 more Smart Citation

WBIN-Tree: A Single Scan Based Complete, Compact and Abstract Tree for Discovering Rare and Frequent Itemset Using Parallel Technique

Rai,

Kumar,

Shetty

et al. 2024

IEEE Access

View full text Add to dashboard Cite

Data analytics is an integral part of strategic decision making in various fields but not limited to business, education, and healthcare systems. Existing research works focus on the discovery of itemsets with rare antecedents and consequent or frequent antecedents and consequent. Analysis of association among itemsets with rare antecedents and frequent consequent is equally important to gain valuable insights before making crucial decisions. Mining these itemsets from large datasets is time and resource intensive process. Expedition in the process of mining aids in quick decision making and hence, the entire dataset needs to be stored in the RAM. In this paper, a novel Weighted Binary Count Tree (WBIN-Tree) is proposed and implemented in CUDA to exploit the power of GPU and discover itemsets with rare antecedent and frequent consequent using parallel approach. WBIN-Tree stores the entire dataset in an abstract, complete, and compact form in the RAM using single database scan. WBIN-Tree is compared with existing sequential and parallel algorithms by varying the data size and dimension. The performance evaluation of WBIN-Tree showed promising results, proving to be the most time and space efficient algorithm to store the entire large dataset in the RAM. However, based on the size of the GPU, the performance drops when executed on datasets with large dimensions which could be handled by processing the attributes in batches. Additionally, a case study is included to understand the importance of mining association rules with rare antecedent and frequent consequent by executing the algorithm on breast cancer dataset.

show abstract

Section: A Dataset Collectionmentioning

confidence: 99%

“…The detection of outliers also ensures the quality of medical data [5]. Apriori [6], FP-Tree [7], PWC-Tree [8] and BIN-Tree [9] are some of the ARM algorithms to discover frequent and rare itemsets in the fields of medicine [10], business [11], and education [12].…”

Section: Introductionmentioning

confidence: 99%

WBIN-Tree: A Single Scan Based Complete, Compact and Abstract Tree for Discovering Rare and Frequent Itemset Using Parallel Technique

Rai,

Kumar,

Shetty

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Comprehensive analysis shows that the students in the experimental class are in the transitional stage from specific calculations to formal calculations [19], as Piaget said. Thinking mainly in images, logical thinking skills have 7 Wireless Communications and Mobile Computing developed to a certain extent, and they begin to have relatively strong self-introspection.…”

Section: The Overall Analysis Of the Distribution Of Intelligencementioning

confidence: 99%

Basic Theory and Practice Teaching Method Based on the Cerebellar Model Articulation Controller Learning Algorithm

Huang

Liu

Zhang

et al. 2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

With the continuous in-depth development of science and technology in my country, the field of artificial intelligence has also made considerable progress. For example, the comprehensiveness and operability of technology have been enhanced. Artificial intelligence, as a comprehensive and intersecting research field in the fields of computer science, information science, and mathematics, has also made a certain contribution to the progress of international students in colleges and universities. This article is aimed at studying the problems based on basic theories and time teaching methods, mainly through a comprehensive data analysis of artificial intelligence technology and fusion differential evolution algorithm, and then improving the learning ability of students and comprehensive quality. This paper proposes a swarm intelligence algorithm, K -means clustering algorithm, and vector machine algorithm and summarizes the process and application fields of the swarm intelligence algorithm. In addition, the CMAC learning algorithm is proposed, which shows that robots under the background of industrial intelligence and machine learning can organize themselves to form groups to perform complex tasks. The experimental results of this paper show that the communication range is between 0 and 1, which can enable more robots to communicate in order to improve the individual’s social learning opportunities, thereby enhancing the individual’s learning ability to improve the performance of learning behavior and improving the efficiency of practical teaching and research, making the efficiency reach 0.9.

show abstract

“…Association rule mining (ARM) is a rule-based machine learning algorithm that can discover hidden patterns and interesting relationships in large databases. Recently, ARM has become a promising technique in multiple fields including biomedical, educational, and social sciences, such as predicting COVID-19 cases and symptom patterns ( 9 , 10 ), the application of multiresource for MOOC teaching ( 11 ), the study of improving English achievement analysis ( 12 ) and the investigation of the relationships between shifts in digital skills and cybersecurity awareness ( 13 ). Common analysis algorithms and evaluation approaches for ARM include the Apriori algorithm ( 14 ), entropy weight method (EWM) ( 15 ), technique for order preference by similarity to ideal solution (TOPSIS) ( 16 ), support vector machine (SVM) and random forest (RF) ( 17 ).…”

Section: Introductionmentioning

confidence: 99%

A novel FCTF evaluation and prediction model for food efficacy based on association rule mining

Liu,

Zhang,

Lin

et al. 2023

Front. Nutr.

View full text Add to dashboard Cite

IntroductionFood-components-target-function (FCTF) is an evaluation and prediction model based on association rule mining (ARM) and network interaction analysis, which is an innovative exploration of interdisciplinary integration in the food field.MethodsUsing the components as the basis, the targets and functions are comprehensively explored in various databases and platforms under the guidance of the ARM concept. The focused active components, key targets and preferred efficacy are then analyzed by different interaction calculations. The FCTF model is particularly suitable for preliminary studies of medicinal plants in remote and poor areas.ResultsThe FCTF model of the local medicinal food Laoxianghuang focuses on the efficacy of digestive system cancers and neurological diseases, with key targets ACE, PTGS2, CYP2C19 and corresponding active components citronellal, trans-nerolidol, linalool, geraniol, α-terpineol, cadinene and α-pinene.DiscussionCenturies of traditional experience point to the efficacy of Laoxianghuang in alleviating digestive disorders, and our established FCTF model of Laoxianghuang not only demonstrates this but also extends to its possible adjunctive efficacy in neurological diseases, which deserves later exploration. The FCTF model is based on the main line of components to target and efficacy and optimizes the research level from different dimensions and aspects of interaction analysis, hoping to make some contribution to the future development of the food discipline.

show abstract

An Association Rule-Based Multiresource Mining Method for MOOC Teaching

Cited by 5 publications

References 18 publications

WBIN-Tree: A Single Scan Based Complete, Compact and Abstract Tree for Discovering Rare and Frequent Itemset Using Parallel Technique

WBIN-Tree: A Single Scan Based Complete, Compact and Abstract Tree for Discovering Rare and Frequent Itemset Using Parallel Technique

Basic Theory and Practice Teaching Method Based on the Cerebellar Model Articulation Controller Learning Algorithm

A novel FCTF evaluation and prediction model for food efficacy based on association rule mining

Contact Info

Product

Resources

About