Paper Info
Title
A Complex Event Processing Toolkit for Detecting Technical Chart Patterns
Abstract
With the advent of large high volume data, we have seen need for real time analytic techniques like Complex Event Processing. This paper extends a Complex Event Processing Engine to support real time identification of technical chart patterns from streaming data. Technical chart patterns are known interesting recurring patterns on time series data, and they are used by experts in time series data analysis domains such as stock market and currency exchange rates. Yet the automated identification of these patterns is challenging due to the high volatility and noise of data. The paper focuses on identifying suitable technique to filter out volatility and a set of algorithms to query the data streams continuously and to identify patterns. The resulting solution is a toolkit for chart pattern recognition which is a composition of a set of complex CEP queries and a Kernel regression smoother applied on moving windows. Same toolkit can be used to detect chart patterns in other domains like Gold and Oil prices etc as well.
Year
DOI
Venue
2015
10.1109/IPDPSW.2015.83
IPDPS Workshops
Keywords
Field
DocType
complex event processing toolkit,technical chart pattern detection,complex event processing engine,real-time technical chart pattern identification,time series data analysis domain,data volatility,data noise,data stream query,chart pattern recognition,complex CEP queries,kernel regression smoother,moving windows
Kernel (linear algebra),Data mining,Time series,Data stream mining,Algorithm design,Computer science,Complex event processing,Chart pattern,Chart,Kernel regression
Conference
Citations 
PageRank 
References 
4
0.47
7
Authors
6
Name
Order
Citations
PageRank
Madhushi Niluka Bandara140.47
Rajitha Madhushan Ranasinghe240.47
Rashmi Woranga Mudugamuwa Arachchi340.47
Channa Gayan Somathilaka440.47
Srinath Perera533232.23
Daya Chinthana Wimalasuriya640.47