A survey of big data in social media using data mining techniques

2015 ◽  
Author(s):  
Sheela Gole ◽  
Bharat Tidke
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Big Data ◽  
Data Mining Techniques ◽  
Using Data

Cardiovascular Disease Prediction Using Data Mining Techniques

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.

scholarly journals Mining on Social Media Data: To Determine the Personality of Unrevealed Person

2019 ◽  
Vol 8 (4) ◽  
pp. 8574-8577
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Information Mining ◽  
Social Media Data ◽  
Data Mining Techniques ◽  
Network Discovery ◽  
The Social ◽  
Mining Methods ◽  
Using Data ◽  
Media Data

The unavoidable utilization of online networking like Facebook is giving exceptional measures of social information. Information mining methods have been broadly used to separate learning from such information. The character of the person is predicted whether he is good or not by using data mining techniques from user self-made data. Mining methods are being broadly using to separate learning from such information, main examples for them are network discovery and slant investigation. Notwithstanding, there is still a lot of room to investigate as far as the occasion information (i.e., occasions with timestamps, for example, posting an inquiry, altering an article in Wikipedia, and remarking on a tweet. These occasions react users' personal conduct standards and working forms in the social media websites.

Cardiovascular Disease Prediction Using Data Mining Techniques

2019 ◽  
pp. 159-179
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.

scholarly journals Analysis of agriculture data using data mining techniques: application of big data

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Jharna Majumdar ◽  
Sneha Naraseeyappa ◽  
Shilpa Ankalaki
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Data Mining Techniques ◽  
Using Data

Summary of Data Reduction Based on Cloud Environment

2014 ◽  
Vol 1079-1080 ◽  
pp. 779-781
Author(s):  
Shu Li Huang
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Big Data ◽  
Data Reduction ◽  
Attribute Reduction ◽  
Cloud Environment ◽  
Mining Technology ◽  
Data Mining Techniques ◽  
Using Data

In today's era of big data, how to quickly find the data they need is a difficult thing from the mass of information, in order to achieve this goal, cloud computing to data mining technology provides a new direction, this article on how cloud environment attribute Reduction using data mining techniques are described.

Mining Big Data in Manufacturing: Requirement Analysis, Tools and Techniques

2014 ◽  
Author(s):  
Utpal Roy ◽  
Bicheng Zhu ◽  
Yunpeng Li ◽  
Heng Zhang ◽  
Omer Yaman
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Product Design ◽  
Literature Study ◽  
Data Mining Techniques ◽  
Using Data ◽  
Tools And Techniques ◽  
Audio Video ◽  
Manufacturing Problems ◽  
Selection Of

Data Mining has tremendous potential and usefulness in improving the effectiveness of decision-making in manufacturing. Tools and techniques of data mining can be intelligently applied from product design analysis to the product repair and maintenance. Vast amount of data in the form of documents (text), graphical formats (CAD-file), audio/video, numbers, figures and/or hypertext are available in any typical manufacturing system. Our ultimate goal is to develop data-driven methodologies to solve manufacturing problems using data mining techniques. As a precursor, based on a literature study, this paper investigates selective manufacturing areas to identify the requirements for applying data mining techniques in solving potential manufacturing problems. The reviewed manufacturing areas are: (i) the “Design Intent” retrieval process for the product design and manufacturing, (ii) selection of materials, (iii) performance evaluations of manufacturing process design and operation management, and (iv) product inspection, and after-sales services (repair and maintenance). Industrial efforts towards addressing “Big Data” issues have also been briefly narrated in this paper. Lastly, the paper discusses two important data–related issues that may affect any applications of the data mining tools and techniques — (i) uncertainty involved in data collection, and (ii) interoperability of data collected at different levels of an enterprise.

scholarly journals Systematic Review on the Suspicious Profiles Detection on Online Social Media Data

2017 ◽  
Vol 10 (3) ◽  
pp. 644-652
Author(s):  
Asha Asha ◽  
Dr. Balkishan
Keyword(s):  
Systematic Review ◽  
Data Mining ◽  
Social Media ◽  
Law Enforcement ◽  
Social Media Data ◽  
Data Mining Techniques ◽  
Online Social Media ◽  
Using Data ◽  
Media Data ◽  
Mining Tools

Escalating crimes on digital facet alarms the law enforcement bodies to keep a gaze on online activities which involve massive amount of data. This will raise a need to detect suspicious activities on online available social media data by optimizing investigations using data mining tools. This paper intends to throw some light on the data mining techniques which are designed and developed for closely examining social media data for suspicious activities and profiles in different domains. Additionally, this study will categorize the techniques under various groups highlighting their important features, challenges and application realm.

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