A CEP-driven framework for real-time news impact prediction on financial markets

Real-time news impact prediction on financial markets is a challenging task for finance experts with limited IT expertise. Many practitioners build machine learning models trained with many low-level features extracted from multiple event-based streams (news and financial market data), which often l...

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Vydáno v:	Service oriented computing and applications Ročník 17; číslo 2; s. 129 - 144
Hlavní autoři:	Chen, Weisi, El Majzoub, Ahmad, Al-Qudah, Islam, Rabhi, Fethi A.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Springer London 01.06.2023 Springer Nature B.V
Témata:	Algorithms Classification Computer Appl. in Administrative Data Processing Computer Science Computer Systems Organization and Communication Networks Data collection Data transmission Datasets Digital currencies e-Commerce/e-business Finance Impact prediction IT in Business Machine learning Management of Computing and Information Systems Manufacturing News News media Pharmaceutical industry Real time Securities markets Sentiment analysis Social networks Software Software Engineering/Programming and Operating Systems Special Issue Paper Subject specialists Windows (intervals) Data quality Real-time analytics Service-oriented architecture Finance Complex event processing Machine learning
ISSN:	1863-2386, 1863-2394
On-line přístup:	Získat plný text
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