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User Generated Content (UGC) has become the fastest growing sector of the WWW. Data mining from UGC presents challenges not typically found in text mining from documents. UGC can be semi-structured and its content can be very short and informal, containing relatively little content similar to a chat or an email conversation. In addition, UGC can be viewed(More)
this paper, a pattern-based stock data mining approach which transforms the numeric stock data to symbolic sequences, carries out sequential and non-sequential association analysis and uses the mined rules in classifying/predicting the further price movements is proposed. Two formulations of the problem are considered. They are intra-stock mining which(More)
is one of the fundamental components in time series data mining. One of the uses of the time series segmentation is trend analysis-to segment the time series into primitive trends like uptrend and downtrend. In this paper, a time series segmentation method based on a specialized binary tree representation scheme is proposed; this representation scheme is(More)
Most of the existing commercial NIDS products are signature-based but not adaptive. In this paper, an adaptive NIDS using data mining technology is developed. Data mining approaches are used to accurately capture the actual behavior of network traffic, and portfolio mined is useful for differentiating "normal" and "attack" traffics. On the other hand, most(More)