The Experts below are selected from a list of 21 Experts worldwide ranked by ideXlab platform

Guangquan Zhang - One of the best experts on this subject based on the ideXlab platform.

  • facets a Cognitive Business intelligence system
    Information Systems, 2013
    Co-Authors: Li Niu, Guangquan Zhang
    Abstract:

    A Cognitive decision support system called FACETS was developed and evaluated based on the situation retrieval (SR) model. The aim of FACETS is to provide decision makers Cognitive decision support in ill-structured decision situations. The design and development of FACETS includes novel concepts, models, algorithms and system architecture, such as ontology and experience representation, situation awareness parsing, data warehouse query construction and guided situation presentation. The experiments showed that FACETS is able to play a significant role in supporting ill-structured decision making through developing and enriching situation awareness.

  • An Exploratory Cognitive Business Intelligence System
    IEEE WIC ACM International Conference on Web Intelligence (WI'07), 2007
    Co-Authors: Jie Lu, Eng Chew, Guangquan Zhang
    Abstract:

    An exploratory study of Web-based Cognitive Business intelligence systems (CBIS) is presented in this paper. The underpinning concepts and theories are situation awareness, mental model, and naturalistic decision making (NDM). The CBIS is an extension of the traditional Business intelligence system with Cognitive orientation. It focuses on developing, enriching, and utilizing the executive's situation awareness, mental models, and other past experience during human-computer interaction, which drives the decision process to approach a naturalistic decision.

Vinod Muthusamy - One of the best experts on this subject based on the ideXlab platform.

  • bpm for the masses empowering participants of Cognitive Business processes
    arXiv: Computers and Society, 2019
    Co-Authors: Aleksander Slominski, Vinod Muthusamy
    Abstract:

    Authoring, developing, monitoring, and analyzing Business processes has requires both domain and IT expertise since Business Process Management tools and practices have focused on enterprise applications and not end users. There are trends, however, that can greatly lower the bar for users to author and analyze their own processes. One emerging trend is the attention on blockchains as a shared ledger for parties collaborating on a process. Transaction logs recorded in a standard schema and stored in the open significantly reduces the effort to monitor and apply advanced process analytics. A second trend is the rapid maturity of machine learning algorithms, in particular deep learning models, and their increasing use in enterprise applications. These Cognitive technologies can be used to generate views and processes customized for an end user so they can modify them and incorporate best practices learned from other users' processes. Keywords: BPM, Cognitive computing, blockchain, privacy, machine learning

  • bpm for the masses empowering participants of Cognitive Business processes
    Business Process Management, 2017
    Co-Authors: Aleksander Slominski, Vinod Muthusamy
    Abstract:

    Authoring, developing, monitoring, and analyzing Business processes has required both domain and IT expertise since Business Process Management tools and practices have focused on enterprise applications and not end users. There are trends, however, that can greatly lower the bar for users to author and analyze their own processes. One emerging trend is the attention on blockchains as a shared ledger for parties collaborating on a process. Transaction logs recorded in a standard schema and stored in the open significantly reduces the effort to monitor and apply advanced process analytics. A second trend is the rapid maturity of machine learning algorithms, in particular deep learning models, and their increasing use in enterprise applications. These Cognitive technologies can be used to generate views and processes customized for an end user so they can modify them and incorporate best practices learned from other users’ processes.

Aleksander Slominski - One of the best experts on this subject based on the ideXlab platform.

  • bpm for the masses empowering participants of Cognitive Business processes
    arXiv: Computers and Society, 2019
    Co-Authors: Aleksander Slominski, Vinod Muthusamy
    Abstract:

    Authoring, developing, monitoring, and analyzing Business processes has requires both domain and IT expertise since Business Process Management tools and practices have focused on enterprise applications and not end users. There are trends, however, that can greatly lower the bar for users to author and analyze their own processes. One emerging trend is the attention on blockchains as a shared ledger for parties collaborating on a process. Transaction logs recorded in a standard schema and stored in the open significantly reduces the effort to monitor and apply advanced process analytics. A second trend is the rapid maturity of machine learning algorithms, in particular deep learning models, and their increasing use in enterprise applications. These Cognitive technologies can be used to generate views and processes customized for an end user so they can modify them and incorporate best practices learned from other users' processes. Keywords: BPM, Cognitive computing, blockchain, privacy, machine learning

  • bpm for the masses empowering participants of Cognitive Business processes
    Business Process Management, 2017
    Co-Authors: Aleksander Slominski, Vinod Muthusamy
    Abstract:

    Authoring, developing, monitoring, and analyzing Business processes has required both domain and IT expertise since Business Process Management tools and practices have focused on enterprise applications and not end users. There are trends, however, that can greatly lower the bar for users to author and analyze their own processes. One emerging trend is the attention on blockchains as a shared ledger for parties collaborating on a process. Transaction logs recorded in a standard schema and stored in the open significantly reduces the effort to monitor and apply advanced process analytics. A second trend is the rapid maturity of machine learning algorithms, in particular deep learning models, and their increasing use in enterprise applications. These Cognitive technologies can be used to generate views and processes customized for an end user so they can modify them and incorporate best practices learned from other users’ processes.

Jie Lu - One of the best experts on this subject based on the ideXlab platform.

  • An Exploratory Cognitive Business Intelligence System
    IEEE WIC ACM International Conference on Web Intelligence (WI'07), 2007
    Co-Authors: Jie Lu, Eng Chew, Guangquan Zhang
    Abstract:

    An exploratory study of Web-based Cognitive Business intelligence systems (CBIS) is presented in this paper. The underpinning concepts and theories are situation awareness, mental model, and naturalistic decision making (NDM). The CBIS is an extension of the traditional Business intelligence system with Cognitive orientation. It focuses on developing, enriching, and utilizing the executive's situation awareness, mental models, and other past experience during human-computer interaction, which drives the decision process to approach a naturalistic decision.

Eng Chew - One of the best experts on this subject based on the ideXlab platform.

  • An Exploratory Cognitive Business Intelligence System
    IEEE WIC ACM International Conference on Web Intelligence (WI'07), 2007
    Co-Authors: Jie Lu, Eng Chew, Guangquan Zhang
    Abstract:

    An exploratory study of Web-based Cognitive Business intelligence systems (CBIS) is presented in this paper. The underpinning concepts and theories are situation awareness, mental model, and naturalistic decision making (NDM). The CBIS is an extension of the traditional Business intelligence system with Cognitive orientation. It focuses on developing, enriching, and utilizing the executive's situation awareness, mental models, and other past experience during human-computer interaction, which drives the decision process to approach a naturalistic decision.