Question 1

Clustering is a common____________ data mining technique

Accepted Answer

A) unsupervised 
B) Supervised 
C) both a & b 
D) None of these 
A) unsupervised 
B) Supervised 
C) both a & b 
D) None of these

Question 2

Which of the following is not a data mining functionality?

Accepted Answer

A) Characterization and Discrimination 
B) Classification and regression 
C) Selection and interpretation 
D) Clustering and Analysis 
A) Characterization and Discrimination 
B) Classification and regression 
C) Selection and interpretation 
D) Clustering and Analysis

Question 3

In____________centrality, the intuition is that the more central nodes are, the more quickly they can reach other nodes.

Accepted Answer

A) Eigenvector 
B) Katz 
C) Closeness 
D) degree 
A) Eigenvector 
B) Katz 
C) Closeness 
D) degree

Question 4

Supervised approaches depend on some a-priori knowledge of the data which are___________

Accepted Answer

A) Class ids 
B) Class labels 
C) Classifiers 
D) None 
A) Class ids 
B) Class labels 
C) Classifiers 
D) None

Question 5

Strategic value of data mining is____________

Accepted Answer

A) cost-sensitive 
B) work-sensitive 
C) time-sensitive 
D) technique-sensitive 
A) cost-sensitive 
B) work-sensitive 
C) time-sensitive 
D) technique-sensitive

Clustering is a common____________ data mining technique

Which of the following is not a data mining functionality?

In____________centrality, the intuition is that the more central nodes are, the more quickly they can reach other nodes.

Supervised approaches depend on some a-priori knowledge of the data which are___________

Strategic value of data mining is____________

Media, Analytics, and Data Mining Techniques

Social Network Analysis and Clustering Algorithms

Network Analysis and Behavior Modeling in Social Media

Exploring User Migration, Security, and Data Mining in Social Media Sites

Data Mining and Clustering: Key Concepts and Tasks

Social Media and Networking

Exploring Network Visualization and Analysis Tools: Techniques, Measures, and Applications

Network Analysis and Individual Behavior: Understanding Centrality, Transitivity, and Social Dynamics

Network Analysis and Social Media

Social Media Analytics and Data Extraction

Social Media Analysis and Modeling Techniques

Various Aspects of Social Media and Prediction Techniques

Filters

Exam 8: Data Mining and Network Analysis: Key Concepts and Techniques

Clustering is a common____________ data mining technique

Which of the following is not a data mining functionality?

In____________centrality, the intuition is that the more central nodes are, the more quickly they can reach other nodes.

Supervised approaches depend on some a-priori knowledge of the data which are___________

Strategic value of data mining is____________

Media, Analytics, and Data Mining Techniques

Social Network Analysis and Clustering Algorithms

Network Analysis and Behavior Modeling in Social Media

Exploring User Migration, Security, and Data Mining in Social Media Sites

Data Mining and Clustering: Key Concepts and Tasks

Social Media and Networking

Exploring Network Visualization and Analysis Tools: Techniques, Measures, and Applications

Network Analysis and Individual Behavior: Understanding Centrality, Transitivity, and Social Dynamics

Network Analysis and Social Media

Social Media Analytics and Data Extraction

Social Media Analysis and Modeling Techniques

Various Aspects of Social Media and Prediction Techniques

Filters