Server-side cross-model measure-based filtering

    公开(公告)号:US11093504B2

    公开(公告)日:2021-08-17

    申请号:US16700434

    申请日:2019-12-02

    Abstract: Some embodiments provide execution of a query on a target data model which is filtered on a measure of a source data model, even if the source data model and the target data model are not logically linked. Some embodiments further support execution of a query on a target data model which is filtered on a measure of a source data model and on a dimension filter of another data model. Some embodiments provide for a substantial amount of query execution to occur on the backend, thereby freeing client resources in comparison to prior approaches.

    Hybrid Online Analytical Processing (OLAP) And Relational Query Processing

    公开(公告)号:US20210089523A1

    公开(公告)日:2021-03-25

    申请号:US16577713

    申请日:2019-09-20

    Abstract: In some embodiments, a method receives a connection to a data source. The method analyzes metadata of the data source to determine a first type of metadata for a first type of database access and a second type of metadata for a second type of database access. The first type of metadata and the second type of metadata are combined into a data structure. Then, the method stores the data structure where the data structure is used to analyze a query to determine which of the first type of database access and the second type of database access to use for the query.

    PRIMARY KEY DETERMINATION
    63.
    发明申请

    公开(公告)号:US20200226111A1

    公开(公告)日:2020-07-16

    申请号:US16247345

    申请日:2019-01-14

    Inventor: Mahsa Imani

    Abstract: A database system includes a first table comprising a plurality of columns and a plurality of column values associated with each of the plurality of columns. For each of the plurality of columns, a structural relationship is determined with each other of the plurality of columns based on the plurality of column values associated with each of the plurality of columns. One or more of the plurality of columns comprising a primary key of the first table are determined based on the structural relationships.

    Interaction relationship building and explorer for dashboard

    公开(公告)号:US10354002B2

    公开(公告)日:2019-07-16

    申请号:US14955068

    申请日:2015-12-01

    Abstract: A technology for building and displaying interaction relationships between visual components of a dashboard is provided. In accordance with one aspect, interaction relationships are defined between the components of the dashboard using a data grid. A relationship may be defined by associating a component to a grid cell and defining a formula in the grid cell based on one or more other grid cells which are further associated to one or more other components. In accordance with another aspect, information of a dashboard including dashboard components, input data and output data in the dashboard is converted into dashboard data models. An interaction relationship graph may be generated based on interactions of the input data and output data of the components. The interaction relationship graph comprises source-to-target relationships between source and target components of the dashboard. The interaction relationship between the visual components of the dashboard may be presented using the dashboard data models containing the source-to-target relationships.

    ARTIFICIAL IMMUNE SYSTEM FOR FUZZY COGNITIVE MAP LEARNING

    公开(公告)号:US20180285769A1

    公开(公告)日:2018-10-04

    申请号:US15475482

    申请日:2017-03-31

    Abstract: The present disclosure involves systems, software, and computer implemented methods for learning relationships between concepts using an artificial immune system. A method includes identifying a set of concepts; determining a state value for each concept at each of a set of time points; generating an initial state and a system response; designating the system response as an antigen a clonal selection algorithm; generating a set of candidate weight matrices to be used as a population of antibodies in the clonal selection algorithm; determining a system response for each antibody; determining an affinity value for each antibody, using the system response for the antibody, the affinity value for a respective antibody representing how closely the respective antibody fits the antigen; cloning a set of antibodies based on the affinity values; repeating the cloning until a stopping point is reached; and selecting a candidate weight matrix with a highest affinity value.

    MACHINE-TRAINED ADAPTIVE CONTENT TARGETING
    69.
    发明申请

    公开(公告)号:US20180211270A1

    公开(公告)日:2018-07-26

    申请号:US15415534

    申请日:2017-01-25

    CPC classification number: G06Q30/0204 G06Q30/0269

    Abstract: Systems and methods for machine-trained adaptive content targeting are provided. The system generates a recommendation model, which includes creating a plurality of offer clusters. Each offer cluster comprises offers having similar features. The system assigns a new offer to one of the plurality of offer clusters. The assigning of the new offer occurs without having to retrain the recommendation model. The system also generates a plurality of user clusters, whereby users within each of the plurality of user clusters share similar behavior. A classification model for predicting an offer cluster from the plurality of offer clusters is created for each of the plurality of user clusters. The system then performs a recommendation process for a new user that includes selecting one or more relevant offers from a predicted offer cluster based on the classification model.

    SYSTEM AND METHOD OF DATA WRANGLING

    公开(公告)号:US20180025051A1

    公开(公告)日:2018-01-25

    申请号:US15720930

    申请日:2017-09-29

    CPC classification number: G06F16/245 G06F3/04847 G06F16/2462 G06F16/35

    Abstract: In some example embodiments, a graphical user interface (GUI) is caused to be displayed on a computing device of a user. The GUI can be configured to enable the user to submit an identification of a dataset and at least one configuration parameter. The identification of the data source, the at least one configuration parameter, and the at least one wrangling parameter can be received via the GUI on the computing device. A sampling algorithm can be configured based on the at least one configuration parameter. A sample of data from the dataset can be generated using the configured sampling algorithm. At least one data wrangling operation can be performed on the sample of data based on the at least one wrangling parameter.

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