Research on anomaly detection algorithm based on sparse variational autoencoder using spike and slab prior by Huahua CHEN, Zhe CHEN

“…Anomaly detection remains to be an essential and extensive research branch in data mining due to its widespread use in a wide range of applications.It helps researchers to obtain vital information and make better decisions about data by detecting abnormal data.Considering that sparse coding can get more powerful features and improve the performance of other tasks, an anomaly detection model based on sparse variational autoencoder was proposed.Firstly, the discrete mixed modelspike and slab distribution was used as the prior of variational autoencoder, simulated the sparsity of the space where the hidden variables were located, and obtained the sparse representation of data characteristics.Secondly, combined with the deep support vector network, the feature space was compressed, and the optimal hypersphere was found to discriminate normal data and abnormal data.And then, the abnormal fraction of the data was measured by the Euclidean distance from the data feature to the center of the hypersphere, and then the abnormal detection was carried out.Finally, the algorithm was evaluated on the benchmark datasets MNIST and Fashion-MNIST, and the experimental results show that the proposed algorithm achieves better effects than the state-of-the-art methods.…”
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Customer Churn Modeling via the Grey Wolf Optimizer and Ensemble Neural Networks by Maryam Rahmaty, Amir Daneshvar, Fariba Salahi, Maryam Ebrahimi, Adel Pourghader Chobar

“…In recent years, many methods have been developed including data mining for predicting the customer churn and manners that customers are likely to behave in the future and therefore, taking action early to prevent their leaving. …”
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Intelligent Integration Algorithm of National Traditional Sports Culture Resources Based on Big Data by Xian-Bin Ai

“…Then, the query set of big data is constructed based on the results of weakly associated data mining, and the query of weakly associated data is completed through data repair. …”
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Implementasi Algoritma Naïve Bayes untuk Mendeteksi Resiko Tinggi Diabetes Melitus Pada Ibu Hamil (Studi Kasus : Puskesmas Kabupaten Malang) by Fatmawati Fatmawati, Satrio Agung Wicaksono, Satrio Hadi Wijoyo

“…Oleh karena itu, Perhatian dan penanganan menyeluruh bagi ibu hamil yang mengalami diabetes. Data mining dapat digunakan untuk deteksi resiko tinggi diabetus mellitus pada ibu hamil. …”
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Analyse du traitement médiatique du silure glane (Silurus glanis), une espèce au centre de controverses by Jean-Marie Bodt, Frédéric Santoul, Muriel Lefebvre

“…By applying lexical data mining, we identified different lexical unities, revealing debates surrounding catfish. …”
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Passenger Flow Path Prediction Based on Urban Rail Transit AFC Data: An Example of Chengdu, China by Yu Wang, Qixuan Qin, Jialiang Chen, Jiangbo Wang, Kai Liu

“…Passengers are divided into two categories based on their travel habits and data mining models, and multinomial logit (MNL) models are separately used to predict their destinations. …”
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Mining EEG with SVM for Understanding Cognitive Underpinnings of Math Problem Solving Strategies by Paul Bosch, Mauricio Herrera, Julio López, Sebastián Maldonado

“…We have developed a new methodology for examining and extracting patterns from brain electric activity by using data mining and machine learning techniques. Data was collected from experiments focused on the study of cognitive processes that might evoke different specific strategies in the resolution of math problems. …”
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Realms of aesthetic experience of classical Chinese gardens based on semantic analysis of online tourism reviews by Mengyuan Xu, Yuanyu Wang, Haitao Yu

“…The novel mixed approach of big data mining and the modeling of aesthetic realms enriched the knowledge of aesthetic experience and provided a new research paradigm for the experiences of cultural heritage by tourists.…”
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Using Clustering Analysis and Association Rule Technology in Cross-Marketing by Yang Cheng, Ming Cheng, Tao Pang, Sizhen Liu

“…The experimental results show that this method can quickly mine the effective information in complex data sets, improve the accuracy and efficiency of data mining, and occupy less memory consumption, which has good theoretical value and application value.…”
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Multimedia Data Processing Technology and Application Based on Deep Learning by Guo Li, Wei Liu

“…In the multimedia data processing, the multimedia data processing technology is obviously superior to the data mining technology and data compression technology. …”
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Financial Early Warning System Model Combining Hybrid Semantic Hierarchy with Group Method of Data Handling Neural Network for Detection of Banks’ Risks by Guangju Li

“…The outcomes of the proposed method when compared to non-data mining methods suggest that it improves accuracy by almost 20%.…”
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Application of Business Intelligence in the Brazilian Educational System by Carlos Grimm Moniz Junior, Tristão Sócrates Baptista Cavalcante, Adalena Kennedy Vieira, Raimundo Kennedy Vieira

“…This is all leveraged to interactive dashboards, which should enable data-driven decisions and forge the way for advanced analytics like data mining. …”
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Machine learning approach to student performance prediction of online learning. by Jing Wang, Yun Yu

“…The ability to improve educational systems using data knowledge has driven the development of the field of educational data mining research. Here, this paper proposes a machine learning method for the prediction of student performance based on online learning. …”
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Design of Mobile Internet Big Data User Behavior Analysis Engine Based on Cloud Computing by Caixia Tao, Xiaojun Xie, Kang Chen, Lirong, Guo, Chun Liu

“…A1ong with the rapid deve1opment of mobi1e internet, te1ecom operators face an increasing1y competition.So traffic operations are imperative for te1ecom operators, and precise marketing based on user behavior ana1ysis is an important means.But in the era of big data, with the rapid growth of the mobi1e internet service and the number of users, the traditiona1 architecture is difficu1t to adapt to the requirements of mass data mining.A design of mobi1e internet big data user behavior ana1ysis engine based on c1oud computing was provided,inc1uding the overa11 system architecture design so1ution, the big data 1oading components and the big data user behavior ana1ysis mode1 components.Additiona11y, the test resu1ts of system performance were ana1yzed.…”
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Sentiment Analysis of Mobile Phone Reviews Using XGBoost and Word Vectors by Wang Zekai

“…Consumer reviews are an important source of data used to judge and examine consumer sentiment, and data mining for reviews of electronic products is an important way to help improve the design of electronic products. …”
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Scholarships Determination to Talented Students Based on Academic Characteristics with Deep Learning Approach and Particle Swarm Optimization Algorithm by Dorota Mozyrska, Ewa Pawluszewicz

“…Therefore, there is a need for a data set of students' information in order to perform a data mining process in order to find those elite students based on their activities and abilities of students and recommend them scholarships. …”
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Modern Technology's role in accounting cost calculation of industrial enterprises: Informatization as a key strategy to improve management efficiency by HuiFang Liang

“…Secondly, it utilizes data mining technology to assist enterprises in cost accounting and efficiency analysis. …”
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Driver anomaly detection in cargo terminal by Shahab Emaani, Abbas Saghaei

“…Subsequently, Isolation Forest, KNN, and HBOS algorithms are applied to detect abnormal behavior using data mining techniques. Results reveal three distinct driver groups, with a notable proportion (98 %) of anomalies concentrated in one group. …”
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The Application of New Educational Concepts in Digital Educational Media by Chun Yang

“…The process is as follows: based on the collected education data, mining the specific factors that will affect the application ability of teachers’ digital education resources and building a multiple machine learning regression model using these objective and significant features to predict the score of teachers’ digital education resources application ability. …”
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EXPLOIT MINING HIGH UTILITY ITEMSETS WITH NEGATIVE UNIT PROFITS FROM VERTICALLY DISTRIBUTED DATABASES by Cao Tùng Anh, Ngô Quốc Huy, Võ Hoàng Khang

“…High Utility Itemset (HUI) mining is an important problem in the data mining literature that considers the utilities for businesses of items (such as profits and margins) that are discovered from transactional databases. …”
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