Advances in Knowledge Discovery in Databases
This book presents recent advances in Knowledge discovery in databases (KDD) with a focus on the areas of market basket database, time-stamped databases and multiple related databases. Various interesting and intelligent algorithms are reported on data mining tasks. A large number of association mea...
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| Main Authors: | , |
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| Corporate Author: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2015.
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| Edition: | 1st ed. 2015. |
| Series: | Intelligent Systems Reference Library,
79 |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-3-319-13212-9 |
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Table of Contents:
- Introduction
- Synthesizing conditional patterns in a database
- Synthesizing arbitrary Boolean expressions induced by frequent itemsets
- Measuring association among items in a database
- Mining association rules induced by item and quantity purchased
- Mining patterns different related databases
- Mining icebergs in different time-stamped data sources.-Synthesizing exceptional patterns in different data Sources
- Clustering items in time-stamped databases
- Synthesizing some extreme association rules from multiple databases
- Clustering local frequency items in multiple data sources
- Mining patterns of select items in different data sources
- Mining calendar-based periodic patterns in time-stamped data
- Measuring influence of an item in time-stamped databases
- Clustering multiple databases induced by local patterns
- Enhancing quality of patterns in multiple related databases
- Concluding remarks.