Insights into the Prevalence of Software Project Defects by Javier Alfonso-Cendón, Manuel Castejón Limas, Joaquín B. Ordieres Meré, Juan Pavón

“…This analysis is based on data that was collected by the International Software Benchmarking Standards Group (ISBSG) on the development of 4,106 software projects. Data mining techniques have been applied to gain a better understanding of the behaviour of the project activities and to identify a link between the effort distribution and the prevalence of software defects. …”
Get full text

Rough decision rules extraction and reduction based on granular computing by Hong-can YAN, Feng ZHANG, Bao-xiang LIU

“…Rule mining was an important research content of data mining,and it was also a hot research topic in the fields of decision support system,artificial intelligence,recommendation system,etc,where attribute reduction and minimal rule set extraction were the key links.Most importantly,the efficiency of extraction was determined by its application.The rough set model and granular computing theory were applied to the decision rule reduction.The decision table was granulated by granulation function,the grain of membership and the concept granular set construction algorithm gener-ated the initial concept granular set.Therefore,attribute reduction could be realized by the distinguish operator of concept granule,and decision rules extraction could be achieved by visualization of concept granule lattice.Experimental result shows that the method is easier to be applied to computer programming and it is more efficient and practical than the existing methods.…”
Get full text

Principal component analysis of time delay in large IP network by Xuan WEI, Xiaoying HUANG

“…Network time delay is one of the key indexes to evaluate network performance.Principal component analysis (PCA) is a kind of multivariable analysis and declination algorithm commonly used in the field of data mining.Based on PCA analysis of time delay in large IP networks, aiming to find out the deep reason of time delay and the interdependencies among nodes of the network, a scientific and reasonable network time delay evaluation system was built, and effective suggestions for IP network construction and optimization were finally got.The off-line analysis of the historical network delay is only a preliminary application of the PCA.In the future, PCA can be applied to the real-time on-line monitoring and analysis of the network performance, such as network traffic, network delay, network packet loss, etc., in combination with the network topology, current network traffic direction, routing, distance and other related factors, thus the efficiency and quality of network operations can be further improved.…”
Get full text

Construction of Personalized Learning Platform Based on Intelligent Algorithm in the Context of Industry Education Integration by Zhifang Qian

“…First, through the method of questionnaire survey to understand the students’ needs for personalized learning and the functions of online teaching platform, on this basis, build a personalized learning platform based on reinforcement learning and data mining intelligent algorithm. The system test results show that when the number of accesses is less than 2000, the CPU and memory resources of the system basically remain unchanged. …”
Get full text

Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming by Palika Chopra, Rajendra Kumar Sharma, Maneek Kumar

“…An effort has been made to develop concrete compressive strength prediction models with the help of two emerging data mining techniques, namely, Artificial Neural Networks (ANNs) and Genetic Programming (GP). …”
Get full text

Research on data integration privacy preservation mechanism for DaaS by Zhi-gang ZHOU, Hong-li ZHANG, Xiang-zhan YU, Pan-pan LI

“…The emergence of cloud computing provides a broader platform for multiple data owners to make integrated data publishing and collaborative data mining. In data-as-a-service (DaaS) model, integrated data was deployed in a cer-tain cloud platform with an untrusted service provider ta privacy leakage has become the challenge hindering applica-tion and popularization of DaaS model. …”
Get full text

Grey Wolf Optimizer Based on Powell Local Optimization Method for Clustering Analysis by Sen Zhang, Yongquan Zhou

“…Clustering is a popular data analysis and data mining technique. Hence, the PGWO could be applied in solving clustering problems. …”
Get full text

Data aggregation and indexing support from multiple sources using graph model in medical expert system databases by A. V. Kurachkin, V. S. Sadau

“…Proposed representation mechanism is also shown to be effective for centralized processing using various data mining and intelligent analysis techniques.…”
Get full text

GPS Position Prediction Method Based on Chaotic Map-Based Flower Pollination Algorithm by Wanjun Yang, Zengwu Sun

Get full text

Event Forecasting in Organizational Networks: A Discrete Dynamical System Approach by Piotr Śliwa

“…The network perspective is believed to successfully model most of the socioeconomic phenomena, which, in combination with the prospects of continuously advancing tools for automated data mining and machine learning, gives a tempting promise to effectively forecast socioeconomic events occurring in our societies and businesses. …”
Get full text

Personalized recommendation model with multi-level latent features by Qing SHEN, Wenbin GUO, Jungang LOU, Qiangguo YU

“…Personalized recommendation has become one of the most effective means to solve information overload, and it is also a hot technology in the research field of massive data mining.However, traditional recommendation algorithms often only use the user’s rating information on the item, and lack a comprehensive consideration of the potential characteristics of the user and the item.The factorization machine, wide neural network, crossover network and deep neural network were combined to extract the shallow latent features, low-order nonlinear latent features, linear cross latent features, and high-order nonlinear latent features of users and items.Thus, a new deep learning personalized recommendation model with multilevel latent features was established.The experimental results on four commonly used data sets show that considering the multi-level potential features of users and items can effectively improve the prediction accuracy of personalized recommendations.Finally, the influence of factors such as the dimensions of the embedding layer and the number of neurons on the prediction performance of the new model was studied.…”
Get full text

Research Progress and Prospect of Reservoir Intelligent Operation by WANG Sen, WANG Xiayu, JIA Wenhao, NI Xiaokuan, LIU Xia

“…Reservoir operation is an important tool to adapt to climate changes and prevent floods and droughts.With the continuously advancing digitization,a new generation of information technology has begun to integrate with traditional reservoir operations.Based on 445 references collected by CNKI from 2000 to 2023 and 412 references in the core collection database of Web of Science,this paper employs CiteSpace to analyze the status and trend of intelligent operation research.Meanwhile,it systematically sorts out two types of operation technologies including model building and model solving,and six types of information technologies containing knowledge graphs,the internet of things,big data,cloud platform,artificial intelligence,and digital twins.Finally,the intelligent operation provides new ideas for reservoir group operation in river basins,but it still needs further breakthroughs in fields such as thorough perception,data mining,universal model building,and intelligent decision-making.…”
Get full text

Application of random forest in big data completion by Zheng WANG, Hua REN, Yanping FANG

“…Telecom operators have a lot of data, but in view of a variety of reasons, the quality of the data is not ideal, there are a lot of data is not complete or even missing. For existing data mining, it is necessary to carry out the data to meet the quality of the data and to achieve sufficient sampling proportion. …”
Get full text

Corrigendum: Predictive factors for the development of depression in children and adolescents: a clinical study by Hong Zhang, Peilin Yu, Xiaoming Liu, Xiaoming Liu, Ke Wang, Ke Wang, Ke Wang, Ke Wang

Get full text

Research on the Application of User Recommendation Based on the Fusion Method of Spatially Complex Location Similarity by Lili Wang, Ting Shi, Shijin Li

Get full text

The High Security Mechanisms Algorithm of Similarity Metrics for Wireless and Mobile Networking by Xingwang Wang

“…Association rules are an important topic in data mining, and they have a broad application prospect in wireless and mobile networking as they can discover interesting correlations between items hidden in a large number of data. …”
Get full text

On Clustering Detection Based on a Quadratic Program in Hypergraphs by Qingsong Tang

“…The determination of clustering structure within hypergraphs is a significant problem in the area of data mining. Various works of detecting clusters on graphs and uniform hypergraphs have been published in the past decades. …”
Get full text

Big Data Analytics: A Tutorial of Some Clustering Techniques by Said Baadel

“…Data Clustering or unsupervised classification is one of the main research areas in Data Mining. Partitioning Clustering involves the partitioning of n objects into k clusters. …”
Get full text

Accelerated aging as a mediator of the association between co-exposure to multiple air pollutants and risk of chronic kidney disease by Shuo Zhang, Yuxin Liu, Jike Qi, Yu Yan, Tongyu Gao, Xin Zhang, Dong Sun, Ting Wang, Ping Zeng

Get full text

Prediksi Stok dan Pengaturan Tata Letak Barang Menggunakan Kombinasi Algoritma Triple Exponential Smoothing dan FP-Growth by Kristoko Dwi Hartomo, Sri Yulianto Prasetyo, Rahmat Abadi Suharjo

“…Pengolahan data dalam penelitian ini disebut data mining dengan menggunakan algoritma FP-Growth dan Triple Exponential Smoothing. …”
Get full text