Research on Data Mining in the Information Network Application

2015 ◽  
Vol 713-715 ◽  
pp. 1839-1842
Author(s):  
Xin Zhao ◽  
Yan Hong Huangfu
Keyword(s):  
Data Mining ◽  
Rapid Development ◽  
Effective Means ◽  
User Preferences ◽  
Turn Of The Century ◽  
Support Network ◽  
Information Network ◽  
Information Platform ◽  
Combining Data ◽  
Network Platform

Turn of the century, with the rapid development of database and network technology, we produce and the ability to collect data has been rapidly increasing, a large amount of data stored in databases and data warehouses, we have been submerged in the vast ocean of data and information. People need to have a new, more effective means to a variety of large amounts of data mining in order to realize their potential, data mining is to generate and rapidly developed applications in such environments, it appears to automatically and intelligently put massive data transformation provides a means for useful information and knowledge. This article will combining data mining and e-commerce, introduced the data in e-commerce information platform mining methods, so as to provide reference for the information network of employees, in order to better analyze the hidden relationships between data and model, master user preferences, provide personalized marketing decisions for decision support network platform, to reduce the risk.

scholarly journals Construction of Multimodal Transport Information Platform

2018 ◽  
Vol 38 ◽  
pp. 04019
Author(s):  
Ya Wang ◽  
Yu Cheng ◽  
Zhi Zhao
Keyword(s):  
Service Quality ◽  
Rapid Development ◽  
Present Situation ◽  
Transport Network ◽  
Information Platform ◽  
Multimodal Transport ◽  
Network Platform ◽  
Opening Process

With the rapid development of economy, the volume of transportation in China is increasing, the opening process of the market is accelerating, the scale of enterprises is expanding, the service quality is being improved, and the container multimodal transport is developing continuously.The hardware infrastructure of container multimodal transport is improved obviously, but the network platform construction of multimodal transport is still insufficient.Taking Shandong region of China as an example, the present situation of container multimodal transport in Shandong area can no longer meet the requirement of rapid development of container, and the construction of network platform needs to be solved urgently. Therefore, this paper will briefly describe the conception of construction of multimodal transport network platform in Shandong area.In order to achieve the rapid development of multimodal transport.

Application of Data Mining Technology in Higher Education

2014 ◽  
Vol 574 ◽  
pp. 743-747
Author(s):  
Xiao Hong Liu
Keyword(s):  
Higher Education ◽  
Data Mining ◽  
Decision Making ◽  
Information Technology ◽  
Rapid Development ◽  
Complete Information ◽  
Focus Of Attention ◽  
Technical Support ◽  
Mining Technology ◽  
Information Platform

With the rapid development of information technology, many universities have a relatively complete information platform, and a mass of data resources. Faced a lot of data, how the data is rational used and developed, to accomplish the transformation of knowledge that provide managers with basis for decision making, has become the focus of attention in universities. Data mining technology provide technical support for achieving this goal.

Research on Communication Automation with Design and Implementation of FTP Based on Serv-U

2013 ◽  
Vol 738 ◽  
pp. 276-279
Author(s):  
Hong Ji
Keyword(s):  
Rapid Development ◽  
Information Resources ◽  
Automation System ◽  
File Transfer ◽  
Security Strategy ◽  
Access Methods ◽  
Information Platform ◽  
Server Software ◽  
Working Principle ◽  
Network Platform

With the rapid development of network technology, communication automation system is widely used. It includes cabling system, broadband network system, mobile phone coverage system, cable and digital communication system. Use of the network is one of the functions of communication automation, and FTP (File Transfer Protocol) is one of the widely used protocols in the Internet. Based on the network platform, people use FTP service to transfer files and share information resources. The paper discusses the construction, working principle and access methods of FTP site. According to the security problems of FTP service, the paper researches on communication automation and proposes the security strategy of FTP technology. Combined with the engineering example, it introduces the concrete steps and methods of setting up FTP server based on server software Serv-U. Using FTP technology, it realizes allocation and rational use of information resources and also constructs a reliable, efficient, unified information platform. The FTP system runs normally.

Data Mining Technique Applied To DNA Sequencing

2015 ◽  
Vol 2 (7) ◽  
pp. 18
Author(s):  
R. Jamuna
Keyword(s):  
Data Mining ◽  
Dna Methylation ◽  
Markov Chain ◽  
Human Genome ◽  
Transition Probabilities ◽  
Markov Chain Model ◽  
Effective Means ◽  
Cpg Islands ◽  
Chain Model ◽  
The Given

CpG islands (CGIs) play a vital role in genome analysis as genomic markers.  Identification of the CpG pair has contributed not only to the prediction of promoters but also to the understanding of the epigenetic causes of cancer. In the human genome [1] wherever the dinucleotides CG occurs the C nucleotide (cytosine) undergoes chemical modifications. There is a relatively high probability of this modification that mutates C into a T. For biologically important reasons the mutation modification process is suppressed in short stretches of the genome, such as ‘start’ regions. In these regions [2] predominant CpG dinucleotides are found than elsewhere. Such regions are called CpG islands. DNA methylation is an effective means by which gene expression is silenced. In normal cells, DNA methylation functions to prevent the expression of imprinted and inactive X chromosome genes. In cancerous cells, DNA methylation inactivates tumor-suppressor genes, as well as DNA repair genes, can disrupt cell-cycle regulation. The most current methods for identifying CGIs suffered from various limitations and involved a lot of human interventions. This paper gives an easy searching technique with data mining of Markov Chain in genes. Markov chain model has been applied to study the probability of occurrence of C-G pair in the given   gene sequence. Maximum Likelihood estimators for the transition probabilities for each model and analgously for the  model has been developed and log odds ratio that is calculated estimates the presence or absence of CpG is lands in the given gene which brings in many  facts for the cancer detection in human genome.

The prediction model of personality in social networks by using data mining deep learning algorithm and random walk model

2020 ◽  
pp. 002072092093683
Author(s):  
Yu Zhu
Keyword(s):  
Data Mining ◽  
Deep Learning ◽  
Social Network ◽  
Random Walk ◽  
Prediction Method ◽  
Random Walk Model ◽  
Personality Characteristics ◽  
User Personality ◽  
Network Platform ◽  
Personality Prediction

The objective is to predict and analyze the behaviors of users in the social network platform by using the personality theory and computational technologies, thereby acquiring the personality characteristics of social network users more effectively. First, social network data are analyzed, which finds that the type of text data marks the majority. By using data mining technology, the raw data of numerous social network users can be obtained. Based on the random walk model, the data information of the text status of social network users is analyzed, and a user personality prediction method integrating multi-label learning is proposed. In addition, the online social network platform Weibo is taken as the research object. The blog information of Weibo users is obtained through crawler technology. Then, the users are labeled in accordance with personality characteristics. The Pearson correlation coefficient is used to evaluate the relation between the user personality characteristics and the user behavior characteristics of the Weibo users. The correlation between the network behaviors and personality characteristics of Weibo users is analyzed, and the scientificity of the prediction method is verified by the Big Five Model of Personality. By applying relevant technologies and algorithms of data mining and deep learning, the learning ability of neural networks on data characteristics can be improved. In terms of performance on analyzing text information of social network users, the user personality prediction method of integrated multi-label learning based on the random walk model has a large advantage. For the problem of personality prediction of social network users, through combining data mining technology and deep neural network technology in deep learning, the data processing results of social network user behaviors are more accurate.

Fault Diagnosis of Automobile ECUs with Data Mining Technologies

2010 ◽  
Vol 40-41 ◽  
pp. 156-161 ◽  
Author(s):  
Yang Li ◽  
Yan Qiang Li ◽  
Zhi Xue Wang
Keyword(s):  
Data Mining ◽  
Fault Diagnosis ◽  
Decision Tree ◽  
Data Stream ◽  
Electronic Control Unit ◽  
Rapid Development ◽  
Reliability And Validity ◽  
Control Unit ◽  
Use Of Data ◽  
The Cost

With the rapid development of automotive ECUs(Electronic Control Unit), the fault diagnosis becomes increasingly complicated. And the link between fault and symptom becomes less obvious. In order to improve the maintenance quality and efficiency, the paper proposes a fault diagnosis approach based on data mining technologies. By making full use of data stream, we firstly extract fault symptom vectors by processing data stream, and then establish a diagnosis decision tree through the ID3 decision tree algorithm, and finally store the link rules between faults and the related symptoms into historical fault database as a foundation for the fault diagnosis. The database provides the basis of trend judgments for a future fault. To verify this approach, an example of diagnosing faults of entertainment ECU is showed. The test result testifies the reliability and validity of this diagnostic method and reduces the cost of ECU diagnosis.

scholarly journals Investigating the Temporal Effect of User Preferences with Application in Movie Recommendation

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Wen-Jun Li ◽  
Qiang Dong ◽  
Yan Fu
Keyword(s):  
Rapid Development ◽  
User Preferences ◽  
Mobile Internet ◽  
Smart Devices ◽  
Data Sets ◽  
Rating Data ◽  
Temporal Effect ◽  
Proposed Model ◽  
Target User ◽  
The Difference

As the rapid development of mobile Internet and smart devices, more and more online content providers begin to collect the preferences of their customers through various apps on mobile devices. These preferences could be largely reflected by the ratings on the online items with explicit scores. Both of positive and negative ratings are helpful for recommender systems to provide relevant items to a target user. Based on the empirical analysis of three real-world movie-rating data sets, we observe that users’ rating criterions change over time, and past positive and negative ratings have different influences on users’ future preferences. Given this, we propose a recommendation model on a session-based temporal graph, considering the difference of long- and short-term preferences, and the different temporal effect of positive and negative ratings. The extensive experiment results validate the significant accuracy improvement of our proposed model compared with the state-of-the-art methods.

scholarly journals Precise Position Intelligent Matching System of Online Recruitment Platform Based on Data Mining Technology

2021 ◽  
Vol 2066 (1) ◽  
pp. 012001
Author(s):  
Zhen Gao
Keyword(s):  
Data Mining ◽  
Rapid Development ◽  
Internet Technology ◽  
Job Seekers ◽  
Mining Technology ◽  
Position Information ◽  
Precise Position ◽  
Random Mass ◽  
Online Recruitment ◽  
Platform System

Abstract With the rapid development of Internet technology and computer technology, network applications have been developed more and more, and have penetrated into all walks of life in society. The emergence of the networking of the talent market has made the scale of online recruitment increase, and the amount of data on the Internet has become larger and larger, and online recruitment has become the main channel for corporate recruitment. Therefore, how to use the massive online recruitment data to quickly and accurately find the corresponding information and explore the hidden knowledge mode is a very valuable research topic. Data mining (DM) is a technology for data analysis for large amounts of data. It can discover hidden, hidden, and potentially useful knowledge hidden in the data from the vague, noisy, and random mass data, and build relevant Model, realize prediction, etc. The characteristics of data mining technology (DMT) are very suitable for the analysis of online recruitment information, research on large amounts of information, and find out the knowledge in it for decision support. This article aims to study the accurate job matching system of the online recruitment platform based on DMT. Based on the analysis of the advantages of online recruitment, related DMT and the design principles of the online recruitment platform system, the data collected by Weka DM tools are analyzed. Analyzing and getting useful job positions is just to provide job seekers and corporate-related recruiters with useful job information. The experimental results show that the online recruitment platform system can complete the collection of online recruitment position information, and can realize the DM function, which has good practical application value.

The Scheme Design of ‘Bi-Speed Bicycle Viaduct’ Demonstration Line

2018 ◽  
Author(s):  
Keli Xiao ◽  
Yanjun Jin ◽  
Aijia Zou ◽  
Lin Li ◽  
Wei He
Keyword(s):  
Traffic Safety ◽  
High Performance ◽  
Bridge Deck ◽  
High Performance Concrete ◽  
Rapid Development ◽  
Effective Means ◽  
Low Carbon ◽  
Scheme Design ◽  
The People ◽  
Continuous Beam Bridge

<p>The bicycle viaduct is an effective method to solve the contradiction between the rapid development of urbanization and low carbon. In this paper, a 4.8km long viaduct was designed between the Happy Valley and Phoenix Peak park of Chengdu, China. The standard sections of the whole viaduct adopt steel box girder and Ultra High Performance Concrete (UHPC) precast beam with 30m spans and 5.5m widths of bridge deck (single). And the UHPC connection plate is used to replace the traditional mechanical telescopic device to realize the continuous bridge deck between the ends of the simple beam, which embodies the concept of ‘green bridge’. This line focuses on the design of three nodes, which includes the five towers cable-stayed bridge, the double deck arch bridge across the Fu River and the continuous beam bridge in leisure area. The three bridges enrich the bridge modelling, reflecting the application of aesthetics in the bridge. The whole traffic is based on bicycle, which adopts separation traffic with double speed of fast and slow speed and can be used for sightseeing and travel. This design highlights the people-oriented, can ensure traffic safety and achieve a ‘safe travel, green travel’. Therefore, the viaduct is an effective means to solve the disharmony between the urban development and the environment.</p>

Instance Selection

2011 ◽  
pp. 1041-1045
Author(s):  
Huan Liu
Keyword(s):  
Data Mining ◽  
Data Storage ◽  
Data Reduction ◽  
Effective Means ◽  
Digital Data ◽  
Data Selection ◽  
Instance Selection ◽  
Redundant Data ◽  
Performance Deterioration ◽  
Digital Data Storage

The amounts of data become increasingly large in recent years as the capacity of digital data storage worldwide has significantly increased. As the size of data grows, the demand for data reduction increases for effective data mining. Instance selection is one of the effective means to data reduction. This article introduces basic concepts of instance selection, its context, necessity and functionality. It briefly reviews the state-of-the-art methods for instance selection. Selection is a necessity in the world surrounding us. It stems from the sheer fact of limited resources. No exception for data mining. Many factors give rise to data selection: data is not purely collected for data mining or for one particular application; there are missing data, redundant data, and errors during collection and storage; and data can be too overwhelming to handle. Instance selection is one effective approach to data selection. It is a process of choosing a subset of data to achieve the original purpose of a data mining application. The ideal outcome of instance selection is a model independent, minimum sample of data that can accomplish tasks with little or no performance deterioration.

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