Please use this identifier to cite or link to this item: http://idr.nitk.ac.in/jspui/handle/123456789/8336
Title: InterTARM: FP-tree based framework for mining inter-transaction association rules from stock market data
Authors: Chhinkaniwala, H.
Santhi Thilagam, P.
Issue Date: 2008
Citation: Proceedings of the International Conference on Computer Science and Information Technology, ICCSIT 2008, 2008, Vol., , pp.513-517
Abstract: Mining association rules from transactions occurred at different time series is a difficult task because of high computational complexity, very large database size and multidimensional attributes. Traditional techniques, such as fundamental and technical analysis can provide investors with tools for predicting stock prices. However, these techniques cannot discover all the possible relations between stocks and thus there is a need for a different approach that will provide a deeper kind of analysis. We propose a framework called InterTARM on real datasets. Our approach employs effective preprocessing, pruning techniques and available condensed data structure to efficiently discover inter-transaction association rules. � 2008 IEEE.
URI: https://idr.nitk.ac.in/jspui/handle/123456789/8336
Appears in Collections:2. Conference Papers

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