MINING TOPIC SIGNAL FROM TEXT USING ARTIFICIAL INTELLIGENCE
N.Tamilarasi| Journal Title | : | Asian Journal of Applied Research |
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| DOI | : | |
| Page No | : | 1-4 |
| Volume | : | 1 |
| Issue | : | 4 |
| Month/Year | : | 4/2015 |
Keywords
Data stream mining, sequence mining, performance, adaptation, improving mining quality.
Abstract
Data stream mining and sequence mining have many applications and pose challenging research problems. Typical applications such as network monitoring, web searching, telephone services and credit card purchases are characterized by the need to mine continuously massive data streams to discover up-to-date patterns, which are invaluable for timely strategic decisions. Also the data processing speed, adaptation of data, noise and mining quality are the problems to overcome. In this work, the author proposed a system which involves adaptive boosting, robust regression ensemble, sequence clustering and mining quality for better data mining.