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  • Open Access


    Design of a Web Crawler for Water Quality Monitoring Data and Data Visualization

    Ziwen Yu1, Jianjun Zhang1,*, Wenwu Tan1, Ziyi Xiong1, Peilun Li1, Liangqing Meng2, Haijun Lin1, Guang Sun3, Peng Guo4

    Journal on Big Data, Vol.4, No.2, pp. 135-143, 2022, DOI:10.32604/jbd.2022.031024

    Abstract Many countries are paying more and more attention to the protection of water resources at present, and how to protect water resources has received extensive attention from society. Water quality monitoring is the key work to water resources protection. How to efficiently collect and analyze water quality monitoring data is an important aspect of water resources protection. In this paper, python programming tools and regular expressions were used to design a web crawler for the acquisition of water quality monitoring data from Global Freshwater Quality Database (GEMStat) sites, and the multi-thread parallelism was added to improve the efficiency in the… More >

  • Open Access


    Study on the Present Situation and Optimization Path of Gamification Design in Chinese University Libraries

    Yuchen Li1, Junyan Zhu1, Yaxian Feng1,*, Xingrui Yang2, Yu Zhou1

    Journal on Big Data, Vol.4, No.2, pp. 125-133, 2022, DOI:10.32604/jbd.2022.030660

    Abstract In this paper, 137 “First-class universities” and “First-class discipline” construction universities in China are selected as the objects of investigation to analyzes the present situation and characteristics of the game design of University Library in China. Taking the university library in other countries as the reference object, this paper compares the differences of the game design of University Library in China and other countries, sums up the deficiency of the gamification service practice in Chinese university libraries. At last, this paper proposes an optimization path of the gamification design of Chinese University Library from six aspects of game type, game… More >

  • Open Access


    Application of Big Data Information Platform in Medical Equipment

    Meiyu Pang*, Cheng Liu

    Journal on Big Data, Vol.4, No.2, pp. 113-123, 2022, DOI:10.32604/jbd.2022.028791

    Abstract The application of big data in the medical device industry mainly refers to the analysis and processing of various medical devices, so as to provide patients with better treatment and rehabilitation services. At present, our country already has a relatively mature and reliable large database system. This article studies the application of medical equipment in the big data information platform. The main methods used in this article are survey method, case analysis method, and interview method. The big data information platform and medical devices are studied from different aspects. The survey results show that 41% of people completely agree with… More >

  • Open Access


    A Survey of Machine Learning for Big Data Processing

    Reem Almutiri*, Sarah Alhabeeb, Sarah Alhumud, Rehan Ullah Khan

    Journal on Big Data, Vol.4, No.2, pp. 97-111, 2022, DOI:10.32604/jbd.2022.028363

    Abstract Today’s world is a data-driven one, with data being produced in vast amounts as a result of the rapid growth of technology that permeates every aspect of our lives. New data processing techniques must be developed and refined over time to gain meaningful insights from this vast continuous volume of produced data in various forms. Machine learning technologies provide promising solutions and potential methods for processing large quantities of data and gaining value from it. This study conducts a literature review on the application of machine learning techniques in big data processing. It provides a general overview of machine learning… More >

  • Open Access


    Social Opinion Network Analytics in Community Based Customer Churn Prediction

    Ayodeji O. J Ibitoye1,*, Olufade F. W Onifade2

    Journal on Big Data, Vol.4, No.2, pp. 87-95, 2022, DOI:10.32604/jbd.2022.024533

    Abstract Community based churn prediction, or the assignment of recognising the influence of a customer’s community in churn prediction has become an important concern for firms in many different industries. While churn prediction until recent times have focused only on transactional dataset (targeted approach), the untargeted approach through product advisement, digital marketing and expressions in customer’s opinion on the social media like Twitter, have not been fully harnessed. Although this data source has become an important influencing factor with lasting impact on churn management. Since Social Network Analysis (SNA) has become a blended approach for churn prediction and management in modern… More >

  • Open Access


    A Noise Extraction Method for Cryo-EM Single-Particle Denoising

    Huanrong Tang1, Sihan Wang1, Jianquan Ouyang1,*, Tianming Liu2

    Journal on Big Data, Vol.4, No.1, pp. 61-76, 2022, DOI:10.32604/jbd.2022.028078

    Abstract Cryo-Electron Microscopy (cryo-EM) has become a powerful method to study the structure and function of biological macromolecules. However, in clustering tasks based on the projection angle of particles in cryo-EM, the noise considerably affects the clustering results. Existing denoising algorithms are ineffective due to the extremely low signal-to-noise ratio (SNR) of cryo-EM images and the complexity of noise types. The noise of a single particle greatly influences the orientation estimation of the subsequent clustering task, and the result of the clustering task directly affects the accuracy of the 3D reconstruction. In this paper, we propose a construction method of cryo-EM… More >

  • Open Access


    Chinese News Text Classification Based on Convolutional Neural Network

    Hanxu Wang, Xin Li*

    Journal on Big Data, Vol.4, No.1, pp. 41-60, 2022, DOI:10.32604/jbd.2022.027717

    Abstract With the explosive growth of Internet text information, the task of text classification is more important. As a part of text classification, Chinese news text classification also plays an important role. In public security work, public opinion news classification is an important topic. Effective and accurate classification of public opinion news is a necessary prerequisite for relevant departments to grasp the situation of public opinion and control the trend of public opinion in time. This paper introduces a combined-convolutional neural network text classification model based on word2vec and improved TF-IDF: firstly, the word vector is trained through word2vec model, then… More >

  • Open Access


    Restoration of Wind Speed in Qinzhou, Guangxi during Typhoon Rammasun

    Aodi Fu1, Mingxuan Zhu2, Wenzheng Yu1,*, Xin Yao1, Hanxiaoya Zhang3

    Journal on Big Data, Vol.4, No.1, pp. 77-86, 2022, DOI:10.32604/jbd.2022.027477

    Abstract In 2014, Typhoon Rammasun invaded Qinzhou, Guangxi, causing damage to the wind tower sensor at 80 m in Qinzhou. In order to restore the wind speed at 80 m at that time, this paper was based on the hourly average wind speed data of the wind tower and meteorological station from 2017–2019, and constructed the wind speed related model of Meteorological Station and the wind measuring tower in Qinzhou, Moreover, this paper Based on the hourly average wind speed data of Qinzhou Meteorological Station in 2014, Restored the hourly average wind speed of the anemometer tower during Rammasun landfalled. The results showed… More >

  • Open Access


    Research and Practice of Telecommunication User Rating Method Based on Machine Learning

    Qian Tang, Hao Chen, Yifei Wei*

    Journal on Big Data, Vol.4, No.1, pp. 27-39, 2022, DOI:10.32604/jbd.2022.026850

    Abstract The machine learning model has advantages in multi-category credit rating classification. It can replace discriminant analysis based on statistical methods, greatly helping credit rating reduce human interference and improve rating efficiency. Therefore, we use a variety of machine learning algorithms to study the credit rating of telecom users. This paper conducts data understanding and preprocessing on Operator Telecom user data, and matches the user’s characteristics and tags based on the time sliding window method. In order to deal with the deviation caused by the imbalance of multi-category data, the SMOTE oversampling method is used to balance the data. Using the… More >

  • Open Access


    A Survey on Methods and Applications of Intelligent Market Basket Analysis Based on Association Rule

    Monerah M. Alawadh*, Ahmed M. Barnawi

    Journal on Big Data, Vol.4, No.1, pp. 1-25, 2022, DOI:10.32604/jbd.2022.021744

    Abstract The market trends rapidly changed over the last two decades. The primary reason is the newly created opportunities and the increased number of competitors competing to grasp market share using business analysis techniques. Market Basket Analysis has a tangible effect in facilitating current change in the market. Market Basket Analysis is one of the famous fields that deal with Big Data and Data Mining applications. MBA initially uses Association Rule Learning (ARL) as a mean for realization. ARL has a beneficial effect in providing a plenty benefit in analyzing the market data and understanding customers’ behavior. An important motive of… More >

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