The Application of Data Mining Technology in the Data Analysis of Traditional Chinese Medicine

2014 ◽  
Vol 687-691 ◽  
pp. 1266-1269
Author(s):  
Zhen Wang ◽  
Kan Kan She
Keyword(s):  
Data Mining ◽  
Information Technology ◽  
Data Analysis ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Rapid Development ◽  
Theoretical Knowledge ◽  
Mining Technology ◽  
Mining Methods ◽  
Using Data

With the rapid development of information technology, the amount of data accumulated by people is increasing sharply. Data mining technology is an effective method to find useful information from vast amounts of data and increase the utilization of information. After thousands of years of development, traditional Chinese medicine has accumulated a wealth of theoretical knowledge and a lot of books and records, more and more Chinese medicine databases are created. Using data mining technology to mine the unknown knowledge and rules and put forward assumptions for experiment and theory can be a good auxiliary research of traditional Chinese medicine. This article analyzes the data mining methods of traditional Chinese medicine at first. Then, the application of data mining technology in traditional Chinese medicine data analysis is introduced which includes the data mining of traditional Chinese medicine literatures, diagnosis and clinic of traditional Chinese medicine and prescription and medication of traditional Chinese medicine. At last, the aspects which need to be paid attention to in the data mining of traditional Chinese medicine are pointed out.

Study on Application of Data Mining Technology in Syndrome Differentiation of TCM

2013 ◽  
Vol 765-767 ◽  
pp. 282-285
Author(s):  
Zhi Guo Dai ◽  
Yang Yang Han
Keyword(s):  
Data Mining ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Association Rules ◽  
Association Rule ◽  
Association Rule Mining ◽  
Syndrome Differentiation ◽  
Rule Mining ◽  
Mining Technology ◽  
Disease Symptoms

Study on the applications of association rule mining in traditional Chinese medicine (TCM) knowledge and experience is carried out in this paper. The association rules of disease symptoms and syndrome differentiation, syndrome differentiation and prescription, disease symptoms and prescription are mined by analyzing the cases of patients with chronic gastritis, and then the mined association rules are interpreted that provide the beneficial reference for data mining technology in TCM.

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.

scholarly journals A review of data mining methods in financial markets

2021 ◽  
Vol 1 (4) ◽  
pp. 362-392
Author(s):  
Haihua Liu ◽  
◽  
Shan Huang ◽  
Peng Wang ◽  
Zejun Li ◽  
...  
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Financial Markets ◽  
Social Life ◽  
Development Trend ◽  
Financial Data ◽  
Support Vector ◽  
Mining Methods ◽  
Financial Data Analysis ◽  
Using Data

<abstract><p>Financial activities are closely related to human social life. Data mining plays an important role in the analysis and prediction of financial markets, especially in the context of the current era of big data. However, it is not simple to use data mining methods in the process of analyzing financial data, due to the differences in the background of researchers in different disciplines. This review summarizes several commonly used data mining methods in financial data analysis. The purpose is to make it easier for researchers in the financial field to use data mining methods and to expand the application scenarios of it used by researchers in the computer field. This review introduces the principles and steps of decision trees, support vector machines, Bayesian, K-nearest neighbors, k-means, Expectation-maximization algorithm, and ensemble learning, and points out their advantages, disadvantages and applicable scenarios. After introducing the algorithms, it summarizes the use of the algorithm in the process of financial data analysis, hoping that readers can get specific examples of using the algorithm. In this review, the difficulties and countermeasures of using data mining methods are summarized, and the development trend of using data mining methods to analyze financial data is predicted.</p></abstract>

scholarly journals Analyze and Enhance Sales in Lulu Supermarket using Data Mining Technology

2020 ◽  
Author(s):  
Ahmed Abdullah Awadh Koofan ◽  
Mohammed Kaleem
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Association Rules ◽  
Association Rule ◽  
Relevant Information ◽  
Research Association ◽  
Mining Technology ◽  
Time Consumption ◽  
Huge Data ◽  
Using Data

-Data mining is a powerful technology for analyzing huge data, it has many techniques such as; classification, clustering, prediction and association rules etc., In this research Association rule will be used for analyzing data, which will help to extract the data related to combinations of items. Numerous customers tends to purchase items regularly, each time they visit supermarket, customer’s need to move around from shelf to shelf for the product of their interest which is time consuming. This research will help to minimize the time consumption for customers by analyzing the customer’s invoices and letting know the supermarket about the patterns of customer's orientations. In this work python tool will be used for data mining, by using association rule to analyze the customer’s purchases and retrieve the relevant information which will help to determine the customer’s pattern and know the association between products. In this rationale, the data of customer’s purchases were collected from Lulu hypermarket for data analysis and the outcomes of the analysis is to know the customer’s patterns and making the shopping easy by reorganizing the related items and the most buying items together on same shelf.

Sign in / Sign up

Export Citation Format

Share Document