A Visual Interactive Analytics Interface for Complex Event Processing and Machine Learning Processing of Financial Market Data
Applying machine learning techniques over streaming data is notoriously difficult as it involves the interplay of several technologies that need to be judiciously put together by IT experts. This has motivated the need to provide intuitive and easy to use interactive interfaces for financial experts...
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| Vydáno v: | Proceedings / International Conference on Information Visualisation s. 189 - 194 |
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| Jazyk: | angličtina |
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IEEE
01.09.2020
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| ISSN: | 2375-0138 |
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| Abstract | Applying machine learning techniques over streaming data is notoriously difficult as it involves the interplay of several technologies that need to be judiciously put together by IT experts. This has motivated the need to provide intuitive and easy to use interactive interfaces for financial experts to be able to leverage both Complex Event Processing (CEP) and Machine Learning (ML) technologies. The solution proposed in this paper is based on an open architecture that uses CEP engines as a pre-processing function for downstream ML training and prediction computations. We demonstrate this approach using a few scenarios involving the analysis of financial market data streams. |
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| AbstractList | Applying machine learning techniques over streaming data is notoriously difficult as it involves the interplay of several technologies that need to be judiciously put together by IT experts. This has motivated the need to provide intuitive and easy to use interactive interfaces for financial experts to be able to leverage both Complex Event Processing (CEP) and Machine Learning (ML) technologies. The solution proposed in this paper is based on an open architecture that uses CEP engines as a pre-processing function for downstream ML training and prediction computations. We demonstrate this approach using a few scenarios involving the analysis of financial market data streams. |
| Author | Berry, Andrew Tri Luong, Nhan Nathan Milosevic, Zoran Rabhi, Fethi |
| Author_xml | – sequence: 1 givenname: Nhan Nathan surname: Tri Luong fullname: Tri Luong, Nhan Nathan email: luongtrinhan@gmail.com organization: Deontik,Brisbane,Australia – sequence: 2 givenname: Zoran surname: Milosevic fullname: Milosevic, Zoran email: zoran@deontik.com organization: Deontik,Brisbane,Australia – sequence: 3 givenname: Andrew surname: Berry fullname: Berry, Andrew email: andyb@deontik.com organization: Deontik,Brisbane,Australia – sequence: 4 givenname: Fethi surname: Rabhi fullname: Rabhi, Fethi email: f.rabhi@unsw.edu.au organization: University of New South Wales,School of Computer Science and Engineering,Sydney,Australia |
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| Snippet | Applying machine learning techniques over streaming data is notoriously difficult as it involves the interplay of several technologies that need to be... |
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| SubjectTerms | artificial intelligence complex event processing Computer architecture Data visualization directional changes Engines financial market data Machine learning real-time analytics streaming Training visual analytics Visualization |
| Title | A Visual Interactive Analytics Interface for Complex Event Processing and Machine Learning Processing of Financial Market Data |
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