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公开(公告)号:US20210349911A1
公开(公告)日:2021-11-11
申请号:US16867036
申请日:2020-05-05
Applicant: BUSINESS OBJECTS SOFTWARE LTD.
Inventor: Ben Murphy , Ying Wu , Paul O'Hara , Emmet Norton , Malte Christian Kaufmann , Orla Cullen
Abstract: The present disclosure involves systems, software, and computer implemented methods for automatically detecting hot areas in heat map visualizations. One example method includes identifying a two-dimensional heat map. The identified two-dimensional heat map is converted to a one-dimensional heat map. Cells of the one-dimensional heat map are clustered using a density-based clustering algorithm to generate at least one dense region of cells. A mean value of cells in each dense region is calculated and the dense regions are sorted by mean value in descending order. An approach for identifying hot areas is selected and the selected approach is used to identify at least one dense region as a hot area of the one-dimensional heat map.
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公开(公告)号:US11727030B2
公开(公告)日:2023-08-15
申请号:US16867036
申请日:2020-05-05
Applicant: BUSINESS OBJECTS SOFTWARE LTD.
Inventor: Ben Murphy , Ying Wu , Paul O'Hara , Emmet Norton , Malte Christian Kaufmann , Orla Cullen
CPC classification number: G06F16/258 , G06F7/14 , G06F16/285
Abstract: The present disclosure involves systems, software, and computer implemented methods for automatically detecting hot areas in heat map visualizations. One example method includes identifying a two-dimensional heat map. The identified two-dimensional heat map is converted to a one-dimensional heat map. Cells of the one-dimensional heat map are clustered using a density-based clustering algorithm to generate at least one dense region of cells. A mean value of cells in each dense region is calculated and the dense regions are sorted by mean value in descending order. An approach for identifying hot areas is selected and the selected approach is used to identify at least one dense region as a hot area of the one-dimensional heat map.
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公开(公告)号:US20180165599A1
公开(公告)日:2018-06-14
申请号:US15376271
申请日:2016-12-12
Applicant: BUSINESS OBJECTS SOFTWARE LTD.
Inventor: Balazs Pete , Declan Kearney , Cathal McGovern , Simon Dornan , Jennifer Keane , Michael Golden , Orla Cullen , Robert McGrath , Shekhar Chhabra , Kerry O'Connor , Malte Christian Kaufmann , John Julian
CPC classification number: G06N20/00 , G06F17/5009
Abstract: Techniques are described for integrating predictive models into applications, to enable the applications to provide predictive functionality. Using the framework according to implementations, predictive models and their supporting libraries may be incorporated into applications without requiring application developers to be knowledgeable regarding the particular features of the predictive models and/or libraries. The framework exposes a common and consistent application programming interface (API) on top of the predictive libraries. Applications can use the API to interact with the predictive models, thus enabling the applications to leverage predictive functionality. Implementations also provide an API which may be used by applications to request the retraining of predictive models.
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