Data Mining Chapter 5 Part 2
Data Mining Quiz: Deep Dive into OLAP and Data Cubes
Test your knowledge on data mining concepts, particularly focusing on OLAP, data cubes, and top-k queries. This quiz is designed for students and professionals who are eager to deepen their understanding of multidimensional data analysis.
- 26 engaging multiple-choice questions
- Learn about key terms and techniques in data mining
- Assess your grasp of complex data structures
What is the purpose of the data cube?
To help with online transaction processing.
To help with online analytical processing of multidimensional queries.
To help with online search processing.
To help with data mining of unstructured data.
What components make up a user-specified preference in a top-k query?
Selection condition only.
Both a selection condition and a ranking function.
Ranking function only.
Neither a selection condition nor a ranking function.
What applications commonly use top-k queries?
Online banking.
Searching web databases
Social media.
Online shopping.
What is the purpose of using cube space in data mining?
To generate features and targets for mining using OLAP queries.
To speed up repeated model construction.
To define the data space for mining using informative dimension hierarchies.
To define arbitrary subsets of data for mining.
How can OLAP queries be used in data mining?
To define arbitrary subsets of data for mining.
To generate features and targets for mining.
To build prediction models for each candidate data space.
To share computation across model construction for different candidates.
What is the purpose of prediction cubes?
To define arbitrary subsets of data for mining.
To generate features and targets for mining.
To identify data subsets that indicate more accurate prediction.
To build prediction models for each candidate data space.
What is a multifeatured cube?
A data cube that only uses simple measures like count() and sum()
A data cube that enables more in-depth analysis with complex queries
A cube that aggregates data based on a single attribute
A type of cube that only aggregates data at a single granularity level
What are exception indicators used for?
To identify cells with expected values
To highlight all cells in a data cube
To identify cells with unexpected values
To make it difficult for users to analyze data cubes
What do the SelfExp, InExp, and PathExp measures indicate?
The expected value of a cell
The degree of surprise of a cell value relative to its expected value
The difference between the highest and lowest cell values in a data cube
The number of dimensions in a data cube
What is the PBE method used for?
To efficiently materialize all cells in a prediction cube
To find the class label that maximizes a scoring function
To exhaustively build models for all cells in a prediction cube
To determine the predictiveness of a set of attributes on a data subset
What is the purpose of exploring cube technology for advanced kinds of queries?
To limit the data cube structure for typical business data warehouse applications
To extend data cube technology for effective processing of advanced queries
To use data cube technology only for geospatial data warehouses
To develop data cubes for basic data types and applications
What is the purpose of using sampling cubes in data cube technology?
To answer queries on sample data such as survey data
To handle the compression and multidimensional analysis of RFID data
To analyze multimedia data containing images and videos
To analyze text databases containing only structure attributes
What is the purpose of the sampling cube in data cube technology?
To calculate the exact mean, standard deviation, and other measures for the sample data
To support OLAP on sample data and compute confidence intervals for multidimensional queries
To handle the compression and multidimensional analysis of RFID data
To store the entire data population and their multidimensional aggregates
What affects the confidence interval size in a query answer according to the document?
The size of the data population and the sample data
The type of data stored in the sampling cube
The variance of the sample data and the sample size
The number of dimensions in the data cube
What is the purpose of intracuboid query expansion?
To expand the size of the data population
To consider nearby cells in parent cuboids
To include more dimensions in the query
To increase the sample size and enhance the reliability of the query answer
Which correlation measure is best suited for nominal data?
Covariance
Pearson’s correlation coefficient
χ2 correlation test
Spearman’s rank correlation coefficient
A prediction cube is a cube structure that stores informative dimension hierarchies used for data minin
True
False
A top-k query is a query that returns the best k results according to a user-specified preference.
True
False
Data cubes can have a large number of cells, making it difficult for users to explore and analyze the data.
True
False
Exception indicators are computed for only some aggregation levels in a data cube.
True
False
OLAP tools are traditionally designed to handle the full data population, but they can be applied to sample data without any challenges
True
False
Sampling data is often used to save on costs, manpower, time, and materials
True
False
A confidence interval is used to indicate the exact value of the true population mean
True
False
The computation involved in computing a confidence interval is always distributive.
True
False
The best candidates for expansion are the dimensions that are strongly correlated with the measure value.
True
False
The two-sample t-test is used to determine whether two samples have the same mean and can be performed with a confidence level as an input.
True
False
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