Data mining for customer service support
In this thesis, the related work on data mining functions, techniques and tools are first reviewed. Text mining techniques and some of the common data mining applications are then discussed. Techniques in decision support and intelligent fault diagnosis are also reviewed. As the customer service...
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| Format: | Theses and Dissertations |
| Language: | English |
| Published: |
2008
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/13592 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | In this thesis, the related work on data mining functions, techniques and
tools are first reviewed. Text mining techniques and some of the common data
mining applications are then discussed. Techniques in decision support and
intelligent fault diagnosis are also reviewed. As the customer service database is
used for mining, the details of various tables of the database are described.
A data mining process using the DBMiner system is proposed to mine the
structured data from the customer service database for decision support. The data
mining process starts with establishing the mining goals. The data tables that are
suitable for mining are then selected and pre-processed to eliminate irrelevant or
noisy data. The pre-processed data are transformed to a suitable form and stored
into a data warehouse. The data mining functions including summarization,
association, classification, prediction and clustering are then performed. Finally, the
results of the mining functions are evaluated. |
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