Concept Hierarchies: Data Mining Systems and Data Warehouse Quiz

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Questions and Answers

What is the purpose of providing users with the flexibility to tailor predefined concept hierarchies?

The purpose is to allow users to customize the predefined hierarchies according to their particular needs, such as defining a fiscal year starting on April 1 or an academic year starting on September 1.

How can concept hierarchies be defined by discretizing or grouping values for a given dimension or attribute?

Concept hierarchies can be defined by creating a set-grouping hierarchy, where values are discretized or grouped into a set of ranges or intervals, and a total or partial order can be defined among the groups.

What are some different ways that concept hierarchies can be provided in a data mining system?

Concept hierarchies can be provided manually by system users, domain experts, or knowledge engineers, or they can be automatically generated based on statistical analysis of the data distribution.

Why might a user prefer to organize the price dimension using a hierarchy of inexpensive, moderately priced, and expensive ranges?

A user may prefer this type of hierarchy based on their particular viewpoint or needs, as the passage states that there may be more than one concept hierarchy for a given attribute or dimension, based on different user viewpoints. Signup and view all the answers

How can the automatic generation of concept hierarchies be used as a preprocessing step for data mining?

The automatic generation of concept hierarchies is discussed in Chapter 3 as a preprocessing step in preparation for data mining, indicating that it can be used to prepare the data for more effective mining. Signup and view all the answers

What is the relationship between concept hierarchies and schema hierarchies in data mining systems?

The passage states that concept hierarchies that are common to many applications, such as for the time dimension, may be predefined in the data mining system, suggesting that these concept hierarchies are part of the overall schema or data model. Signup and view all the answers

What is a major concern for SDBs regarding concept hierarchies?

Privacy issues Signup and view all the answers

What is the purpose of a starnet model in querying multidimensional databases?

To represent concept hierarchies for dimensions Signup and view all the answers

What do footprints represent in the context of a starnet model?

Abstraction levels of a dimension Signup and view all the answers

Give an example of a concept hierarchy involving several attributes.

Location hierarchy Signup and view all the answers

What operations can footprints in a starnet model support?

Drill-down and roll-up Signup and view all the answers

What distinguishes OLAP systems from SDBs in terms of data handling?

Efficiently handling huge amounts of data Signup and view all the answers

What is the key difference between a schema hierarchy and a concept hierarchy in the context of data warehousing?

A schema hierarchy is a total or partial order among attributes in a database schema, while a concept hierarchy represents relationships between different levels of concepts or entities, such as 'street < city < province or state < country'. Signup and view all the answers

How can hierarchies be automatically generated in a data warehouse?

Hierarchies can be automatically generated based on the analysis of data values and their relationships, such as detecting that certain values represent higher-level concepts or aggregations of other values. Signup and view all the answers

Explain the concept of a set-grouping hierarchy with an example.

A set-grouping hierarchy is a hierarchy where a single child value can belong to multiple parent values. For example, in a product hierarchy, a particular product may belong to multiple product categories or lines. Signup and view all the answers

How can user-defined hierarchies be useful in a data warehouse?

User-defined hierarchies allow analysts and end-users to define custom hierarchical structures based on their specific analysis needs, which may not be captured by the schema or automatically generated hierarchies. Signup and view all the answers

What is the purpose of having hierarchical structures in data warehousing?

Hierarchical structures in data warehousing allow for efficient data aggregation and drill-down/roll-up operations, enabling analysts to view data at different levels of granularity and explore relationships between different levels of data. Signup and view all the answers

Explain the concept of a lattice structure in the context of data warehouse dimensions, using the example provided in the text.

A lattice structure represents a partial order among attributes in a dimension, where multiple attributes can be at the same level. The example shows a lattice for the time dimension, where 'day < {month < quarter; week} < year', indicating that month and quarter are at the same level, along with week. Signup and view all the answers

Study Notes

Concept Hierarchies in Data Mining Systems

Concept hierarchies that are common to many applications (e.g., time) may be predefined in the data mining system.
Users should have the flexibility to tailor predefined hierarchies according to their particular needs.
Concept hierarchies may be defined by discretizing or grouping values for a given dimension or attribute, resulting in a set-grouping hierarchy.
A total or partial order can be defined among groups of values.

Set-Grouping Hierarchy

An example of a set-grouping hierarchy is shown in Figure 4.11 for the dimension price.
Intervals (e.g., $X...$Y ]) denote the range from $X (exclusive) to $Y (inclusive).

Multiple Concept Hierarchies

There may be more than one concept hierarchy for a given attribute or dimension, based on different user viewpoints.
Users may prefer to organize price by defining ranges for inexpensive, moderately priced, and expensive.

Generating Concept Hierarchies

Concept hierarchies may be provided manually by system users, domain experts, or knowledge engineers.
Concept hierarchies may be automatically generated based on statistical analysis of the data distribution.

StarNet Query Model for Querying Multidimensional Databases

The querying of multidimensional databases can be based on a StarNet model, which consists of radial lines emanating from a central point.
Each line represents a concept hierarchy for a dimension.
Each abstraction level in the hierarchy is called a footprint.

Footprints and Abstraction Levels

Footprints represent the granularities available for use by OLAP operations such as drill-down and roll-up.
Example: the time line has four footprints: “day,” “month,” “quarter,” and “year.”

Concept Hierarchy Involving Multiple Attributes

A concept hierarchy may involve a single attribute (e.g., date for the time hierarchy) or several attributes (e.g., the concept hierarchy for location).
Attributes are related by a total order, forming a concept hierarchy such as “street < city < province or state < country.”

Lattice Structures

Alternatively, the attributes of a dimension may be organized in a partial order, forming a lattice.
Example: a lattice for the time dimension based on the attributes day, week, month, quarter, and year is “day < {month < quarter; week} < year.”

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Description

Learn about the importance of predefined concept hierarchies in data mining systems and how users can tailor them to meet their specific needs. Explore how concept hierarchies can be defined by grouping values for dimensions or attributes, providing a set-group for analysis.

Data Mining Systems and Concept Hierarchies

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