The impact of big data market segmentation using data mining and clustering techniques

Using data mining techniques, this study analyzes the influence and dependance of bacterial communities that are determined in routine monitoring of open water quality status, such as heterotrophic bacteria (psychrophiles and mesophiles). The SeLaR database was used, which, in addition to various studies of integrated data related to the reservoirs of Serbia, is the basis for advanced data analysis – utilizing statistical methods and data mining. Data for reservoirs with different morphometric qualities, different positions, trophic status, and dominant bacterial community were analyzed. In this research, classification, and analysis of influential parameters, as well as scenario analysis was applied. The results indicate that a designed data mining system can analyze the state and influence of bacterial communities with different parameters that are determined both in standard routine analysis, and in some more specialized studies. This study showed that designed data mining system can serve as flexible, effective, and practical tool for monitoring water quality using bacterial communities in reservoirs.

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Cardiovascular Disease Prediction Using Data Mining Techniques

Coronary and Cardiothoracic Critical Care ◽

10.4018/978-1-5225-8185-7.ch013 ◽

2019 ◽

pp. 246-264

Author(s):

Kalyani Kadam ◽

Pooja Vinayak Kamat ◽

Amita P. Malav

Keyword(s):

Data Mining ◽

Cardiovascular Disease ◽

Big Data ◽

Cardiovascular Diseases ◽

Primary Objective ◽

Disease Prediction ◽

Data Mining Techniques ◽

Data Architecture ◽

Life Threatening ◽

Using Data

Cardiovascular diseases (CVDs) have turned out to be one of the life-threatening diseases in recent times. The key to effectively managing this is to analyze a huge amount of datasets and effectively mine it to predict and further prevent heart-related diseases. The primary objective of this chapter is to understand and survey various information mining strategies to efficiently determine occurrence of CVDs and also propose a big data architecture for the same. The authors make use of Apache Spark for the implementation.

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Using the Flipped Classroom to Improve Knowledge Creation of Master's-Level Students in Engineering

Computer-Assisted Language Learning ◽

10.4018/978-1-5225-7663-1.ch051 ◽

2019 ◽

pp. 1079-1092 ◽

Cited By ~ 1

Author(s):

Sachin Ahuja

Keyword(s):

Data Mining ◽

Blended Learning ◽

Knowledge Creation ◽

Flipped Classroom ◽

Learning Strategy ◽

Master's Level ◽

Undergraduate Level ◽

Instructional Content ◽

Using Data ◽

The Impact

Student engagement in traditional teacher centered model of teaching is limited to independent working or working in a small group on a task designed by the teacher. Flipped classroom is a blended learning strategy that reverses the traditional educational arrangement by delivering instructional content, often online, outside of the classroom and moves activities, including those that may have traditionally been considered homework, into the classroom. Various studies support and recommend flipped model of teaching at graduate and undergraduate level but very less have analyzed the impact of flipped classroom on academic performance and especially knowledge creation at post graduate level. In this paper we are analyzing the performance and knowledge creation of master's level students using Data Mining Techniques in a flipped classroom model.

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An Assessment of the Impact of Rheological Properties on Rate of Penetration Using Data Mining Techniques

10.2523/19446-ms ◽

2019 ◽

Author(s):

Abo Taleb T. Al-Hameedi ◽

Husam H. Alkinani ◽

Shari Dunn-Norman ◽

Ralph E. Flori ◽

Mortadha T. Alsaba ◽

...

Keyword(s):

Data Mining ◽

Rheological Properties ◽

Rate Of Penetration ◽

Data Mining Techniques ◽

Using Data ◽

The Impact

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Big Data Analytics Using Data Mining Techniques: A Survey

Communications in Computer and Information Science - Advanced Informatics for Computing Research ◽

10.1007/978-981-13-3140-4_24 ◽

2018 ◽

pp. 264-273 ◽

Cited By ~ 1

Author(s):

Shweta Mittal ◽

Om Prakash Sangwan

Keyword(s):

Data Mining ◽

Big Data ◽

Data Analytics ◽

Big Data Analytics ◽

Data Mining Techniques ◽

Using Data

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An Assessment of the Impact of Rheological Properties on Rate of Penetration Using Data Mining Techniques

10.2523/iptc-19446-ms ◽

2019 ◽

Author(s):

Abo Taleb T. Al-Hameedi ◽

Husam H. Alkinani ◽

Shari Dunn-Norman ◽

Ralph E. Flori ◽

Mortadha T. Alsaba ◽

...

Keyword(s):

Data Mining ◽

Rheological Properties ◽

Rate Of Penetration ◽

Data Mining Techniques ◽

Using Data ◽

The Impact

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A Proposed Model for Predicting Employees’ Performance Using Data Mining Techniques

Journal of Computational and Theoretical Nanoscience ◽

10.1166/jctn.2020.9274 ◽

2020 ◽

Vol 17 (8) ◽

pp. 3804-3809

Author(s):

A. Yovan Felix ◽

Karthik Reddy Vuyyuru ◽

Viswas Puli

Keyword(s):

Data Mining ◽

Resource Management ◽

Human Resource Management ◽

Human Resource ◽

Human Resource Professionals ◽

Quality Factors ◽

Proposed Model ◽

Opportune Time ◽

Using Data ◽

The Impact

Human Resource Management has gotten one of the basic pastimes of supervisors and chiefs in practically wide variety of corporations to include plans for accurately locating profoundly qualified representatives. In similar way, administrations come to be intrigued about the presentation of these representatives. Particularly to guarantee the fitting person apportioned to the beneficial employment on the opportune time. From right here the enthusiasm of statistics in mining process has been growing that its goal is disclosure of facts from huge measures of statistics. Three fundamental Data Mining strategies were applied for building the arrangement version and distinguishing the quality factors that emphatically impact the exhibition. To get a profoundly actual version, a few trials were achieved dependent on the beyond procedures which can be actualized in WEKA tool for empowering leaders and Human Resource professionals to anticipate and improve the exhibition of their representatives. This paper makes use of Hadoop for the remedy of great measure of data with which may be guaranteed to be able to decide the impact.

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