MO-A-BRD-09: A Data-Mining Algorithm for Large Scale Analysis of Dose-Outcome Relationships in a Database of Irradiated Head-And-Neck (HN) Cancer Patients

2014 ◽  
Vol 41 (6Part24) ◽  
pp. 410-410
Author(s):  
SP Robertson ◽  
H Quon ◽  
AP Kiess ◽  
JA Moore ◽  
W Yang ◽  
...  
Keyword(s):  
Data Mining ◽  
Head And Neck ◽  
Cancer Patients ◽  
Large Scale ◽  
Data Mining Algorithm ◽  
Scale Analysis ◽  
Mining Algorithm ◽  
Large Scale Analysis

scholarly journals A data-mining framework for large scale analysis of dose-outcome relationships in a database of irradiated head and neck cancer patients

2015 ◽  
Vol 42 (7) ◽  
pp. 4329-4337 ◽  
Author(s):  
Scott P. Robertson ◽  
Harry Quon ◽  
Ana P. Kiess ◽  
Joseph A. Moore ◽  
Wuyang Yang ◽  
...  
Keyword(s):  
Data Mining ◽  
Head And Neck Cancer ◽  
Head And Neck ◽  
Cancer Patients ◽  
Neck Cancer ◽  
Large Scale ◽  
Scale Analysis ◽  
Large Scale Analysis

Research on Association Rule Mining Algorithm Based on Distributed Data

2014 ◽  
Vol 998-999 ◽  
pp. 899-902 ◽  
Author(s):  
Cheng Luo ◽  
Ying Chen
Keyword(s):  
Data Mining ◽  
Association Rule ◽  
Association Rule Mining ◽  
Large Scale ◽  
Frequent Itemsets ◽  
Network Communication ◽  
Data Mining Algorithm ◽  
Distributed Data ◽  
Rule Mining ◽  
Mining Algorithm

Existing data miming algorithms have mostly implemented data mining under centralized environment, but the large-scale database exists in the distributed form. According to the existing problem of the distributed data mining algorithm FDM and its improved algorithms, which exist the problem that the frequent itemsets are lost and network communication cost too much. This paper proposes a association rule mining algorithm based on distributed data (ARADD). The mapping marks the array mechanism is included in the ARADD algorithm, which can not only keep the integrity of the frequent itemsets, but also reduces the cost of network communication. The efficiency of algorithm is proved in the experiment.

scholarly journals Human Resource Allocation Based on Fuzzy Data Mining Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
You Wu ◽  
Zheng Wang ◽  
Shengqi Wang
Keyword(s):  
Data Mining ◽  
Human Resource ◽  
Business Process ◽  
Association Rule ◽  
Association Rule Mining ◽  
Large Scale ◽  
Data Mining Algorithm ◽  
Rule Mining ◽  
Mining Algorithm ◽  
Database Technology

Data mining is currently a frontier research topic in the field of information and database technology. It is recognized as one of the most promising key technologies. Data mining involves multiple technologies, such as mathematical statistics, fuzzy theory, neural networks, and artificial intelligence, with relatively high technical content. The realization is also difficult. In this article, we have studied the basic concepts, processes, and algorithms of association rule mining technology. Aiming at large-scale database applications, in order to improve the efficiency of data mining, we proposed an incremental association rule mining algorithm based on clustering, that is, using fast clustering. First, the feasibility of realizing performance appraisal data mining is studied; then, the business process needed to realize the information system is analyzed, the business process-related links and the corresponding data input interface are designed, and then the data process to realize the data processing is designed, including data foundation and database model. Aiming at the high efficiency of large-scale database mining, database development tools are used to implement the specific system settings and program design of this algorithm. Incorporated into the human resource management system of colleges and universities, they carried out successful association broadcasting, realized visualization, and finally discovered valuable information.

scholarly journals EP-2064 A novel method for GTV generation for large-scale analysis of lung cancer patients planned with 4DCT

2019 ◽  
Vol 133 ◽  
pp. S1136-S1137
Author(s):  
A. Davey ◽  
M. Van Herk ◽  
C. Faivre-Finn ◽  
S. Brown ◽  
A. McWilliam
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Large Scale ◽  
Scale Analysis ◽  
Lung Cancer Patients ◽  
Large Scale Analysis ◽  
Novel Method

scholarly journals Analysis of the Impact of Big Data on E-Commerce in Cloud Computing Environment

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Rongrui Yu ◽  
Chunqiong Wu ◽  
Bingwen Yan ◽  
Baoqin Yu ◽  
Xiukao Zhou ◽  
...  
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Data Storage ◽  
Large Scale ◽  
Query Language ◽  
Optimal Path ◽  
Data Mining Algorithm ◽  
Advantages And Disadvantages ◽  
Mining Algorithm ◽  
The Impact

This article starts with the analysis of the existing electronic commerce system, summarizes its characteristics, and analyzes and solves its existing problems. Firstly, the characteristics of the relational database My Structured Query Language (MySQL) and the distributed database HBase are analyzed, their respective advantages and disadvantages are summarized, and the advantages and disadvantages of each are taken into account when storing data. My SQL is used to store structured business data in the system, while HBase is used to store unstructured data such as pictures. These two storage mechanisms together constitute a data storage subsystem. Secondly, considering the large amount of data in the e-commerce system and the complex calculation of the data mining algorithm, this paper uses MapReduce to realize the parallelization of the data mining algorithm and builds a Hadoop-based commodity recommendation subsystem on this basis. We use JavaEE technology to design a full-featured web mall system. Finally, based on the impact of cloud computing, mobile e-commerce is analyzed, including relevant theories, service mode, architecture, core technology, and the application in e-commerce, which can realize e-commerce precision marketing, find the optimal path of logistics, and take effective security measures to avoid transaction risks. This method can avoid the disadvantages of the traditional e-commerce, where large-scale data cannot be processed in a timely manner, realize the value of mining data behind, and realize the precision marketing of e-commerce enterprises.

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