Behavious based computer user clustering using rough set theory
In the context of information technology nowadays, there are many data were emerged when people are using computers, we called it computer user behavior. All of this data are scrambled over inside the computer such as user behavior log files. The problem with this is, when we want to know the user b...
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| Format: | Undergraduates Project Papers |
| Language: | English |
| Published: |
2013
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| Online Access: | http://umpir.ump.edu.my/id/eprint/7576/ http://umpir.ump.edu.my/id/eprint/7576/ http://umpir.ump.edu.my/id/eprint/7576/1/WANG_LE_WEI.PDF |
| Summary: | In the context of information technology nowadays, there are many data were emerged when people are using computers, we called it computer user behavior. All of this data are scrambled over inside the computer such as user behavior log files. The problem with this is, when we want to know the user behaviors on computer and doing analysis for specific proposes, we normally needed the data only such as program name and opening time, there are too many to look for and they are all scrambled in log files. Therefore, there are techniques that are proposed that will provide a way to automatically mine the data and obtain only meaningful data from the huge data over the internet. The area discussed in this research is Knowledge Discovery in Databases (KDD) and the technique used is Minimum-Minimum Roughness (MMR). The dataset used will be the dataset of computer user log files. By using this MMR technique, I intended to cluster the user log files dataset which each cluster will contain the data most related to each other. |
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