- Year not given
Architecture of data mining system
Short answer
A typical data mining system has source repositories, a database or warehouse server, a knowledge base, a data mining engine, a pattern evaluation module and a user interface. The server fetches relevant data; the engine performs mining functions; evaluation filters patterns using interestingness measures; the UI lets users specify tasks and view results.
Explain the architecture of a typical data mining system.
A typical data mining system has the following components:
+--------------------------------------+
| Graphical user interface |
+------------------+-------------------+
|
+------------------+-------------------+
| Pattern evaluation |<--+
+------------------+-------------------+ |
| | Knowledge
+------------------+-------------------+ | base
| Data mining engine |<--+
+------------------+-------------------+
|
+------------------+-------------------+
| Database / data warehouse server |
+------+-----------------------+-------+
| data cleaning, integration, selection
+------+-----+ +--------+ +----+-----+
| Databases | | DW | | WWW/other|
+------------+ +--------+ +----------+
- Database, data warehouse, web or other repositories: the sources. Cleaning and integration may be applied on them.
- Database or warehouse server: fetches the data relevant to the mining request.
- Knowledge base: domain knowledge that guides the search or evaluates patterns: concept hierarchies, user beliefs, thresholds, metadata.
- Data mining engine: the core; a set of modules for characterisation, association, classification, clustering, prediction and outlier analysis.
- Pattern evaluation module: uses interestingness measures (support, confidence) to filter out uninteresting patterns, and interacts with the mining engine to focus the search.
- User interface: lets the user specify the task, browse results, and visualise patterns in tables, charts or rules.
✓ Answer checked by Claude Opus 5.5 (high effort)
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