Pattern recognition in time series database: A case study on financial database

Authors:
Yan-Ping Huang;Chung-Chian Hsu;Sheng-Hsuan Wang
Affiliations:
Department of Information Management, National Yunlin University of Science and Technology, 123, Sec. 3, University Road, Douliu, Yunlin 640, Taiwan, R.O.C. and Department of Management Informatio ...;Department of Information Management, National Yunlin University of Science and Technology, 123, Sec. 3, University Road, Douliu, Yunlin 640, Taiwan, R.O.C.;Department of Information Management, National Yunlin University of Science and Technology, 123, Sec. 3, University Road, Douliu, Yunlin 640, Taiwan, R.O.C.
Venue:
Expert Systems with Applications: An International Journal
Year:
2007

Citing 5
Cited 6

Mining association rules between sets of items in large databases

SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Data mining: concepts and techniques

Data mining: concepts and techniques
Data visualisation and manifold mapping using the ViSOM

Neural Networks - New developments in self-organizing maps
An Integrated Framework for Visualized and Exploratory Pattern Discovery in Mixed Data

IEEE Transactions on Knowledge and Data Engineering
ViSOM - a novel method for multivariate data projection and structure visualization

IEEE Transactions on Neural Networks

Review: Expert systems and evolutionary computing for financial investing: A review

Expert Systems with Applications: An International Journal
A dynamic data granulation through adjustable fuzzy clustering

Pattern Recognition Letters
Using neural networks and data mining techniques for the financial distress prediction model

Expert Systems with Applications: An International Journal
WMCA: a weighted matrix coverage based approach to cluster multivariate time series

ICNC'09 Proceedings of the 5th international conference on Natural computation
A novel statistical time-series pattern based interval forecasting strategy for activity durations in workflow systems

Journal of Systems and Software
Mining association rules from time series to explain failures in a hot-dip galvanizing steel line

Computers and Industrial Engineering

Quantified Score

Hi-index	12.05

Visualization

Abstract

Today, there are more and more time series data that coexist with other data. These data exist in useful and understandable patterns. Data management of time series data must take into account an integrated approach. However, many researches face numeric data attributes. Therefore, the need for time series data mining tool has become extremely important. The purpose of this paper is to provide a novel pattern in mining architecture with mixed attributes that uses a systematic approach in the financial database information mining. Time series pattern mining (TSPM) architecture combines the extended visualization-induced self-organizing map algorithm and the extended Naive Bayesian algorithm. This mining architecture can simulate human intelligence and discover patterns automatically. The TSPM approach also demonstrates good returns in pattern research.