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Design of Adaptive Business Rules Model for High Frequency Data Processing

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F14%3APU112024" target="_blank" >RIV/00216305:26230/14:PU112024 - isvavai.cz</a>

  • Result on the web

    <a href="http://www.fit.vutbr.cz/research/pubs/all.php?id=10669" target="_blank" >http://www.fit.vutbr.cz/research/pubs/all.php?id=10669</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Design of Adaptive Business Rules Model for High Frequency Data Processing

  • Original language description

    In this paper we would like to discuss high frequency data processing and the use of complex event platform in combination with business rules approach. For such a high volume of data, it is suitable to use complex event platform (CEP), because CEP allows for big data processing in real time. We would like to focus on improvement of decision making process under the condition of dynamical adaptation of the process on the fly. We will use pattern recognition for detecting and predicting the trends in data by mining this information from historical data. After the distinguishing patterns we will build the set of business rules according to which the process runs and we will control the process flow by defining the restrictions. We would like to use this model for building trading systems. Algorithmic trading applies complex event processing by calculating complex algorithms that indicate when to sell or buy based on real-time processing. Market data can be viewed as events. This data needs to be analyzed in real time in order to identify the trends in data and to react to these trends automatically. Traditional approach for detecting anomalies on stock market has been statistical analysis, but a CEP-based approach is able to react faster than the traditional approach.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2014

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    ISAT Monograph Series

  • ISBN

    978-83-7493-346-9

  • ISSN

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    1-10

  • Publisher name

    Wroclaw University of Technology

  • Place of publication

    Szklarska Poręba

  • Event location

    SZKLARSKA PORĘBA

  • Event date

    Jul 21, 2014

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article