Combining Adaptive Resonance Theory and K-Means Method for Data Clustering - On-line Game as an Example
碩士 === 玄奘大學 === 資訊科學學系碩士班 === 96 === The application in company is more and more extensive at Data Mining and Neural Network. The company can use these method to digging new customer and preserving old customer. In Data mining and Adaptive Resonance Theory, data clustering is the most used. This art...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2007
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| Online Access: | http://ndltd.ncl.edu.tw/handle/20381069759338972309 |
| Summary: | 碩士 === 玄奘大學 === 資訊科學學系碩士班 === 96 === The application in company is more and more extensive at Data Mining and Neural Network. The company can use these method to digging new customer and preserving old customer. In Data mining and Adaptive Resonance Theory, data clustering is the most used. This article mainly inquired into the difference of data clustering, advantage ,and disadvantage between K-means of data mining and ART of neural network. And we combined and compared similar each other when we assumed the clustering value number fix for 5% with two method. This research also used the data of a set of network game questionnaire to treating for two methods. We compared the original data and clustering with ART and K-means. We find best hiving off for the way of advocating peace to make K-means subsidiary with ART. Through the explanation of this case, we can prove that relatively accord with the view that this research institute puts forward.
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