scholarly journals Construction of Network Behavior Analysis System of Mobile User Based on Big Data Technology

2016 ◽  
Author(s):  
Haiyan Luo ◽  
Tao Yang ◽  
Qiong Wu
Keyword(s):  
Big Data ◽  
Behavior Analysis ◽  
Mobile User ◽  
Network Behavior ◽  
Analysis System ◽  
Big Data Technology

Design and implementation of bilingual digital reader based on artificial intelligence and big data technology

2020 ◽  
Vol 20 (3) ◽  
pp. 889-907
Author(s):  
Keliang Chen ◽  
Yunxiao Zu ◽  
Yansong Cui
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Behavior Analysis ◽  
Information Services ◽  
Reading Level ◽  
Digital Reading ◽  
Reading Behavior ◽  
User Behavior Analysis ◽  
Reading System ◽  
Big Data Technology

Along with the development of computer and information technology and the arrival of the digital reading wave, more and more users have switched the way they meet their reading needs to digital reading systems, At the same time, a variety of digital reading systems have also been created. However, most digital reading systems focus on how to present a better reading style, but little research has been done on how to use artificial intelligence and big data technology to provide intelligent information services and user behavior analysis. In such a large environment, a digital reading system that can provide reading behavior collection and intelligent analysis, while providing intelligent reading analysis function, will have broad research prospects. The digital reading system studied in this paper can provide reading behavior analysis and intelligent recommendation service for professional users based on artificial intelligence and big data technology. At the same time, the system uses artificial intelligence technology to realize the functions of bilingual learning reading, new word induction records, etc., which can provide users with knowledge efficiency. In addition, the system utilizes big data technology to provide users with information services such as communication content exchange. The main innovations of this digital reading system are computer automatic clauses based on Chinese and English syntax features, data layering processing mechanism that takes into account the speed and quality of book analysis, and book encryption and decryption schemes across computer systems. The system is based on a C/S and B/S fusion architecture and includes a reading system based on PC and Android.It can present customized ePub electronic resources, and collect users’ reading behavior through mobile screen or mouse and other devices, then use artificial intelligence and big data technology to analyze user data, and finally generate user reading reports. At present, the whole system has been applied in many universities, and the reading level of students and the work efficiency of teachers have been greatly improved, which proves that this digital reading system has high practical value.

Research and Design of a Massive Offline Data Analysis System Based on Hadoop

2014 ◽  
Vol 631-632 ◽  
pp. 1049-1052
Author(s):  
Sen Pan ◽  
Li Peng Zhu ◽  
Bin Hu ◽  
Pei Yang
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Research Direction ◽  
Core Function ◽  
Data Platform ◽  
Function Module ◽  
Analysis System ◽  
Data Analysis System ◽  
Research And Design ◽  
Big Data Technology

According to the rapid growth of the scale of the data at present, the traditional model of data analysis based on stand-alone can't meet to the storage and processing of massive data. With the rise of big data technology, integrating the traditional method of data analysis with big data platform to improve the efficiency of data analysis has become a research direction. This paper analyzes the integration of offline data processing and the Hadoop HDFS, MapReduce, designs a large offline data analysis system platform based on Hadoop, and introduces the core function module.

scholarly journals Portable Smart Spectrometer Integrated with Blockchain and Big Data Technology

2019 ◽  
Vol 9 (16) ◽  
pp. 3279
Author(s):  
Yin ◽  
Yang ◽  
Hong ◽  
Cai ◽  
Yu
Keyword(s):  
Big Data ◽  
Spectral Analysis ◽  
Spectral Data ◽  
Analysis Data ◽  
The Internet ◽  
Blockchain Technology ◽  
Big Data Technologies ◽  
Analysis System ◽  
Analysis Models ◽  
Big Data Technology

A portable smart spectrometer (PSS-1.0) and related systems have been designed and implemented to provide rapid on-site spectral analysis and lower the operator knowledge threshold for the application of spectrometry. The PSS-1.0 employs spectral analysis models downloaded from the spectral analysis system for offline spectral analysis and displays the results in the field. Users are incentivized to upload spectral analysis data to the Internet for storage by big data technologies, so that the spectral data can be reused easily. By employing blockchain technology it can be ensured that the data has not been tampered with, which can be used in monitoring and data transaction scenarios. The design of this spectrometer and related systems can be used for regulatory uses that require spectroscopy. Experimental results are presented in this paper, which prove that the design of the PSS-1.0 is feasible. The purpose of this paper is to design a civilian and non-operator knowledge threshold spectrometer and provide some ideas for better processing and utilization of spectral data.

scholarly journals Prospects for Using Big Data in Financial Analysis

2021 ◽  
Vol 110 ◽  
pp. 05004
Author(s):  
Igor Sadyrin ◽  
Olga Syrovatskay ◽  
Olga Leonova
Keyword(s):  
Big Data ◽  
Economic Activity ◽  
Financial Analysis ◽  
Digital Technologies ◽  
Digital Transformation ◽  
Maximum Effect ◽  
Economic Activities ◽  
Analysis System ◽  
Effective Use ◽  
Big Data Technology

The ongoing digital transformation of the national economy inevitably sets the task of introducing digital technologies and tools into the practice of economic activities of organizations and enterprises. One of the areas of digitalization is Big Data technology, which in many ways is already being used in the field of finance. However, for the effective use of big data in the practice of financial analysis of economic activity, it is necessary to solve a variety of significant problems. The article discusses the promising directions of using big data in financial analysis procedures, which, being integrated into the system of forming various management decisions, can significantly increase their efficiency. The necessary elements of the financial analysis system, which, first of all, should be focused on the use of big data, are considered, as well as aspects that, when using digital technologies, can provide the maximum effect.

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