Scientific research and statistics system based on data mining

2014 ◽  
Author(s):  
Xiaojie Zhang
Keyword(s):  
Data Mining ◽  
Scientific Research

Article 2—Definitions

2021 ◽  
pp. 23-24
Author(s):  
Eleonora Rosati
Keyword(s):  
Data Mining ◽  
Subject Matter ◽  
Scientific Research ◽  
University Research ◽  
Public Access ◽  
Educational Activities ◽  
Analytical Technique ◽  
Content Sharing ◽  
Definition Of ◽  
Text And Data Mining

This chapter provides the definition of terms covered in Article 2 of Directive 2019/790 regarding copyright in the Digital Single Market in Europe. It begins with the term 'research organisation', which means a university, research institute, or any other entity that conduct scientific research or carry out educational activities involving the conduct of scientific research. It also explains text and data mining, which is an automated analytical technique that analyses text and data in digital form in order to generate information about patterns, trends, and correlations. The chapter defines cultural heritage institution as a publicly accessible library or museum, an archive, or a film or audio heritage institution, while press publication means a collection of literary works of a journalistic nature. It describes the tasks of an online content-sharing service provider, such as providing information society service that store and give public access to a large amount of copyright-protected works or other protected subject matter uploaded by its users.

scholarly journals Intellectual Analysis of Textual Information in Domain Fields in the System of e-Government

2019 ◽  
pp. 46-52
Author(s):  
T. I. Makarevich
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Text Mining ◽  
Scientific Research ◽  
Textual Information ◽  
Mining Technology ◽  
Analysis Methods ◽  
The Republic ◽  
Linguistic Approaches ◽  
The Given

The given paper considers application of data mining technology in scientific research as one of intellectual analysis methods in the domain field of e-Government. The topicality of the issue is stipulated by the current absence of the researches of the kind in the Republic of Belarus. The paper illustrates how the programme package Rapid Miner and the language R have been applied in text mining. Concept indexing has been admitted as the most resultative form of analyzing domain field ontologies. Formal and linguistic approaches are found most effective in analyzing domain field ontologies. The paper identifies the problems of word redundancy and word polysemy. The prognosis for the further research investigation is in interconnectivity of specialized ontologies studying heterogeneous terms on the basis of artificial intelligence (AI).

scholarly journals The High Security Mechanisms Algorithm of Similarity Metrics for Wireless and Mobile Networking

2017 ◽  
Vol 2017 ◽  
pp. 1-6
Author(s):  
Xingwang Wang
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Association Rules ◽  
Scientific Research ◽  
Security And Privacy ◽  
Similarity Metrics ◽  
Human Society ◽  
Social Production ◽  
Broad Application ◽  
Mobile Networking

With the development of human society and the development of Internet of things, wireless and mobile networking have been applied to every field of scientific research and social production. In this scenario, security and privacy have become the decisive factors. The traditional safety mechanisms give criminals an opportunity to exploit. 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. Apriori, the most influential algorithm of association rules mining, needs to scan a database many times, and the efficiency is low when the database is huge. To solve the security mechanisms problem and improve the efficiency, this paper proposes a new algorithm. The new algorithm scans the database only one time and the scale of data to deal with is getting smaller and smaller with the algorithm running. Experiment results show that the new algorithm can efficiently discover useful association rules when applied to data.

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