Data Mining and Knowledge Management Application to Enhance Business Operations: An Exploratory Study

2018 ◽  
pp. 570-583
Author(s):  
Zeba Mahmood
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Exploratory Study ◽  
Business Operations ◽  
Management Application

scholarly journals Application of Data Mining and Knowledge Management for Business Improvement: An Exploratory Study

2015 ◽  
Vol 8 (3) ◽  
pp. 13-19 ◽  
Author(s):  
Lawal Lawal ◽  
N.T. A. ◽  
Odeniyi Odeniyi ◽  
O. A. ◽  
Kayode Kayode ◽  
...  
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Exploratory Study

scholarly journals Using Data Mining Techniques to Develop Knowledge Management in Organizations: A Review.

2017 ◽  
Vol 7 (2) ◽  
pp. 80-89
Author(s):  
Bagher Dastyar ◽  
◽  
Hanieh Kazemnejad ◽  
Alireza Asgari Sereshgi ◽  
Mohammad Amin Jabalameli ◽  
...  
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Data Mining Techniques ◽  
Using Data

scholarly journals Impact of Knowledge Management Infrastructure on Intellectual Capital

2018 ◽  
Vol 2 (2) ◽  
pp. 185-199
Author(s):  
Khaled Zaidan Abdul Hadi ◽  
Rawia Mohamed Wajih Jarges
Keyword(s):  
Knowledge Management ◽  
Statistical Methods ◽  
Intellectual Capital ◽  
Exploratory Study ◽  
Research Problem ◽  
Overall Performance ◽  
The Impact ◽  
Descriptive Method ◽  
Design And Construction

The research aims to demonstrate the impact of knowledge management infrastructure in intellectual capital through a exploratory study of the views of a sample of individuals in the Institute of Management / Rusafa. The interest in the knowledge management infrastructure contributes to increasing the effectiveness of the intellectual capital of the research sample. The research problem focused on the following questions: Is there a clear perception in the researched organization about the knowledge management infrastructure? Is there a clear perception in the researched organization about intellectual capital? What is the nature of the correlation and influence relationships between the knowledge management infrastructure and the intellectual capital? In order to answer the above questions, the analytical descriptive method was adopted through the design and construction of a scale that has the ability to measure the main dimensions of the research. The questionnaire (35) was distributed by means of an objective sample for a number of teachers as the research sample. In order to analyze the data, a set of statistical methods was used. The research found a significant correlation between the infrastructure of knowledge management and intellectual capital. A number of suggestions were made, including the need to pay attention to the knowledge management infrastructure, which would positively affect the intellectual capital of individuals and the overall performance of the researched organization.

scholarly journals Research on flow patterns of tourists in scenic spots based on Data Mining

2020 ◽  
Vol 214 ◽  
pp. 01014
Author(s):  
Zhao Yingju
Keyword(s):  
Data Mining ◽  
Exploratory Study ◽  
Nature Reserve ◽  
Diffusion Theory ◽  
Travel Speed ◽  
Flow Patterns ◽  
Mobile App ◽  
Theoretical Contribution ◽  
Scenic Spot ◽  
Object Based

For the fixed tourist routes in the scenic spot, the longer the journey is, the slower the speed is, and the easier the congestion is. This study is an exploratory study. In this paper, Yudaokou grassland forest scenic area, a nature reserve crossed by national No.1 scenic road, is selected as the research object. Based on the point- axis gradual diffusion theory, the mobile app is used to record the travel process of tourists on the same tourist route in the same scenic area, so as to calculate the travel speed of tourists on different road sections, and then predict the future congestion of the scenic area, the smaller the speed, the greater the probability of congestion; the greater the speed, the less time, the smaller the probability of congestion. Finally, the paper discusses the significance and theoretical contribution of the study on the two aspects of tourists’ moving behavior and moving mode in scenic spots.

Data mining in anti-money laundering field

2017 ◽  
Vol 20 (3) ◽  
pp. 301-310 ◽  
Author(s):  
Noriaki Yasaka
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Money Laundering ◽  
Design Methodology ◽  
Point Of View ◽  
Important Task ◽  
Content Type ◽  
Suspicious Transaction ◽  
Mining Methods ◽  
The Creation

Purpose This report aims to focus on how suspicious transaction report is created with data mining methods and used from the point of view of knowledge management. Design/methodology/approach This paper considers data mining versus knowledge management in the anti-money laundering (AML) field. Findings In the AML field, the information and knowledge gained are not necessarily used for or shared with the related shareholders. Creating and co-evolving the network of “knowledge professionals” is the impending assignment in this industry. The first and most important task is knowledge management in the global AML field. Originality/value The report considers the creation with data mining methods and utilization from the point of view of knowledge management.

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