scholarly journals The Data Mining Technology Applications for Modeling the Unevenness of Socio-Economic Development of Regions

2020 ◽  
Vol 3 (506) ◽  
pp. 82-91
Author(s):  
L. O. Chagovets ◽  
◽  
V. V. Chahovets ◽  
A. S. Didenko ◽  
◽  
...  
Keyword(s):  
Data Mining ◽  
Economic Development ◽  
Mining Technology ◽  
Socio Economic Development ◽  
Technology Applications

Big Data Dilemmas

2015 ◽  
pp. 10-34
Author(s):  
Debashis “Deb” Aikat
Keyword(s):  
Data Mining ◽  
Economic Development ◽  
Big Data ◽  
Common Good ◽  
Code Of Conduct ◽  
Theory And Practice ◽  
Ethical Values ◽  
Big Data Mining ◽  
Socio Economic Development ◽  
Ethical Role

This chapter delineates the theory and practice of ethical big data mining for socio-economic development in four parts. The first part enunciates the ethical role of big data mining for socio-economic development by theorizing big data as a 20th Century phenomenon and its surging significance in the 21st Century digital era. The second part elucidates ethical values relating to big data mining with particular emphasis on the interplay of theory and practice. The third part connects classical theories of ethics to propose a code of conduct that relates to core ethical values such as privacy, confidentiality, objectivity, transparency, conflict of interest, and common good. The fourth and final part identifies privacy as a major challenge of ethical big data mining and postulates needed research directions. This chapter also features a list of additional reading and big data terms with concise definitions explicating their relevance to big data mining for socio-economic development.

Ethical and Legal Data Mining

2013 ◽  
pp. 201-229 ◽  
Author(s):  
Ben Tran
Keyword(s):  
Data Mining ◽  
Economic Development ◽  
Organizational Development ◽  
Specific Information ◽  
Data Mining Techniques ◽  
Community Or ◽  
Socio Economic Development ◽  
Practical Recommendations

In the process of data mining, techniques used, and results gathered, became ethically or even legally questionable due to the concern of the violation of individuals’ privacy when specific information is obtained, manipulated, and disseminated by other entities without an individual’s knowledge or consent. In other words, it is not the concern of what data is being mined, but more so regarding who is the miner of these data. This chapter is based on a review of the existing studies, which shows that not enough attention has been paid to the study of the “miner,” as well as the ethical and legal qualifications of the miner, from the perspectives of organizational development practitioners (OD) and organizational psychologists (OP) in approaching for certifying or licensing. During the review, several cases are being included to justify the certifying or licensing approach, thus upholding ethical data mining, especially in relation to the socio-economic development of a community, or county. This research concludes with a few practical recommendations for both data miner(s) and entities that are involved with data mining.

Data Mining Technology Applications in Tobacco Commercial Enterprise

2012 ◽  
Vol 461 ◽  
pp. 418-420
Author(s):  
Yi Min Mo ◽  
Xin Shun Tong ◽  
Li Hua Yang
Keyword(s):  
Data Mining ◽  
Data Processing ◽  
Demand Forecasting ◽  
Customer Relationship ◽  
Complex Data ◽  
Market Demand ◽  
Mining Technology ◽  
Technology Applications ◽  
Commercial Enterprise ◽  
Key Issues

The wide application of information technology has greatly improve the work efficiency but also caused a large and complex data accumulation. How to get the valuable information from vast amounts of data are the key issues in data processing. This paper studied the application of data mining technology in tobacco commercial enterprise from three aspects: market demand forecasting, customer relationship management and historical data processing. Analysis of how to use data mining technology to make full use of large amounts of data to provide a basis for tobacco commercial enterprise’s decision-making.

Reuse of Excess Research Data for New Researches

2015 ◽  
pp. 1993-2005
Author(s):  
Amiram Porath
Keyword(s):  
Data Mining ◽  
Economic Development ◽  
Research Data ◽  
Ethical Aspects ◽  
Potential Harm ◽  
The Public ◽  
Current Trends ◽  
Socio Economic Development ◽  
Potential Benefits ◽  
Development Processes

The chapter presents a specific niche dilemma regarding the ethical aspects of utilization of data gathered for one specific research for another research, which was not specified to the data suppliers (sample) at the time of gathering, or that the data suppliers were not even informed of the possibility of such occurrence. That dilemma of the reuse of research data stems from motives that are also (among others) rooted in the aim to increase the public good, and the dilemma is between potential benefits and potential harm. As the forces that create the dilemma are growing in concurrence with current trends in research and research financing, the dilemma commands some attention, even if it seems at first glance to be minor compared to issues related to business data mining and governmental data bases. The discussion ends with a possible solution, but the reader is encouraged to think about the dilemma and understand it rather than “solve” it. The novice can regard this as an introduction to the dilemma while the experienced researcher will view it as a summary. However, this sort of research need to be supported to uphold the ethical aspects of data mining and their various applications in the socio-economic development processes of a country, such as generic or specific researches, entrepreneurship development through innovation, and trading, commerce or e-governance through the utilization of innovative technologies.

Ethical and Legal Data Mining

2015 ◽  
pp. 361-388 ◽  
Author(s):  
Ben Tran
Keyword(s):  
Data Mining ◽  
Economic Development ◽  
Organizational Development ◽  
Specific Information ◽  
Data Mining Techniques ◽  
Community Or ◽  
Socio Economic Development ◽  
Practical Recommendations

In the process of data mining, techniques used, and results gathered, became ethically or even legally questionable due to the concern of the violation of individuals' privacy when specific information is obtained, manipulated, and disseminated by other entities without an individual's knowledge or consent. In other words, it is not the concern of what data is being mined, but more so regarding who is the miner of these data. This chapter is based on a review of the existing studies, which shows that not enough attention has been paid to the study of the “miner,” as well as the ethical and legal qualifications of the miner, from the perspectives of organizational development practitioners (OD) and organizational psychologists (OP) in approaching for certifying or licensing. During the review, several cases are being included to justify the certifying or licensing approach, thus upholding ethical data mining, especially in relation to the socio-economic development of a community, or county. This research concludes with a few practical recommendations for both data miner(s) and entities that are involved with data mining.

Clustering Analysis Based on Data Mining Applications

2013 ◽  
Vol 303-306 ◽  
pp. 1026-1029
Author(s):  
Xue Dong Fan
Keyword(s):  
Data Mining ◽  
Pattern Recognition ◽  
Working Conditions ◽  
Clustering Analysis ◽  
Clustering Algorithm ◽  
Mining Technology ◽  
Noise Characteristics ◽  
Recognition Algorithms ◽  
Technology Applications ◽  
Selection Of

Abstract. In this paper, a clustering algorithm based on data mining technology applications, the use of the extraction mode noise characteristics amount and pattern recognition algorithms, extraction and selection of the characteristic quantities of the three types of mode, carried out under the same working conditions data mining clustering analysis ultimately satisfying recognition.

Big Data Dilemmas

2013 ◽  
pp. 106-130
Author(s):  
Debashis “Deb” Aikat
Keyword(s):  
Data Mining ◽  
Economic Development ◽  
Big Data ◽  
Common Good ◽  
Code Of Conduct ◽  
Theory And Practice ◽  
Ethical Values ◽  
Big Data Mining ◽  
Socio Economic Development ◽  
Ethical Role

This chapter delineates the theory and practice of ethical big data mining for socio-economic development in four parts. The first part enunciates the ethical role of big data mining for socio-economic development by theorizing big data as a 20th Century phenomenon and its surging significance in the 21st Century digital era. The second part elucidates ethical values relating to big data mining with particular emphasis on the interplay of theory and practice. The third part connects classical theories of ethics to propose a code of conduct that relates to core ethical values such as privacy, confidentiality, objectivity, transparency, conflict of interest, and common good. The fourth and final part identifies privacy as a major challenge of ethical big data mining and postulates needed research directions. This chapter also features a list of additional reading and big data terms with concise definitions explicating their relevance to big data mining for socio-economic development.

Reuse of Excess Research Data for New Researches

2013 ◽  
pp. 40-52 ◽  
Author(s):  
Amiram Porath
Keyword(s):  
Data Mining ◽  
Economic Development ◽  
Research Data ◽  
Ethical Aspects ◽  
Potential Harm ◽  
The Public ◽  
Current Trends ◽  
Socio Economic Development ◽  
Potential Benefits ◽  
Development Processes

The chapter presents a specific niche dilemma regarding the ethical aspects of utilization of data gathered for one specific research for another research, which was not specified to the data suppliers (sample) at the time of gathering, or that the data suppliers were not even informed of the possibility of such occurrence. That dilemma of the reuse of research data stems from motives that are also (among others) rooted in the aim to increase the public good, and the dilemma is between potential benefits and potential harm. As the forces that create the dilemma are growing in concurrence with current trends in research and research financing, the dilemma commands some attention, even if it seems at first glance to be minor compared to issues related to business data mining and governmental data bases. The discussion ends with a possible solution, but the reader is encouraged to think about the dilemma and understand it rather than “solve” it. The novice can regard this as an introduction to the dilemma while the experienced researcher will view it as a summary. However, this sort of research need to be supported to uphold the ethical aspects of data mining and their various applications in the socio-economic development processes of a country, such as generic or specific researches, entrepreneurship development through innovation, and trading, commerce or e-governance through the utilization of innovative technologies.

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