公开(公告)号：US07664777B2

公开(公告)日：2010-02-16

申请号：US11671443

申请日：2007-02-05

Applicant: Jean-Yves Cras ,  Henri Biestro ,  Ricardo Polo-Malouvier

Inventor： Jean-Yves Cras ,  Henri Biestro ,  Ricardo Polo-Malouvier

IPC: G06F17/30

CPC classification number: G06F17/30592 ,  G06F17/30398 ,  Y10S707/99932 ,  Y10S707/99943 ,  Y10S707/99944 ,  Y10S707/99945

Abstract: A Relational Database Management System (RDBMS) having any arbitrary structure is translated into a multi-dimensional data model suitable for performing OLAP operations upon. If a relational table defining the relational model includes any tables with cardinality of 1,1 or 0,1, the tables are merged into a single table. If the relational table is not normalized, then normalization is performed and a relationship between the original table and the normalized table is created. If the relational table is normalized, but not by dependence between columns, such as in the dimension table in a snowflake schema, the normalization process is performed using the foreign key in order to generate the normalized table. Once the normalized table is generated, OLAP measures are derived from the normalized relational table by an automated method. In addition, OLAP dimensions are derived from the normalized relational table and the results of the OLAP measures derivation by an automated method according to the present invention. According to an aspect, it is possible to associate a member of a dimension to another member of the same or another dimension. According to another aspect, it is possible to create a new dimension of analysis, the members of which are all the different values that a scalar expression can take on. According to yet another aspect, it is possible to access the various instances of a Reporting Object as members in an OLAP dimension. According to the yet another aspect, it is possible to apply opaque filters or a combination of them to the data that underlies analysis.

Abstract translation: 具有任意结构的关系数据库管理系统（RDBMS）被翻译成适用于执行OLAP操作的多维数据模型。 如果定义关系模型的关系表包含基数为1,1或0,1的任何表，则表被合并到单个表中。 如果关系表未被归一化，则执行归一化，并且创建原始表与归一化表之间的关系。 如果关系表被归一化，而不是列之间的依赖，例如在雪花模式的维度表中，则使用外键执行归一化过程以生成归一化表。 一旦生成了规范化表，就可以通过自动化方法从归一化关系表导出OLAP度量。 另外，从归一化关系表导出OLAP维度，并且通过根据本发明的自动化方法推导OLAP测量结果。 根据一个方面，可以将尺寸的构件与相同或另一维度的另一个构件相关联。 根据另一方面，可以创建分析的新维度，其成员是标量表达式可以承担的所有不同的值。 根据另一方面，可以将报告对象的各种实例作为OLAP维度中的成员访问。 根据另一方面，可以将不透明滤光片或它们的组合应用于基于分析的数据。

公开(公告)号：US07640261B2

公开(公告)日：2009-12-29

申请号：US11454254

申请日：2006-06-16

Applicant: Andrey Belyy ,  Alexander Ocher

Inventor： Andrey Belyy ,  Alexander Ocher

IPC: G06F17/30

CPC classification number: G06F17/30569 ,  Y10S707/99942

Abstract: A computer readable medium is configured to receive an identification of a plurality of data records, where each data record corresponds to one of a plurality of data record schemas represented in COBOL, and each data record schema corresponds to one of a plurality of standardized data record schemas. The computer readable medium is further configured to specify one of the plurality of standardized data record schemas as a selected standardized data record schema, and to process the plurality of data records based on the selected standardized data record schema.

Abstract translation: 计算机可读介质被配置为接收多个数据记录的标识，其中每个数据记录对应于以COBOL表示的多个数据记录模式之一，并且每个数据记录模式对应于多个标准化数据记录中的一个 模式 所述计算机可读介质还被配置为将所述多个标准化数据记录模式中的一个指定为所选择的标准数据记录模式，并且基于所选择的标准化数据记录模式来处理所述多个数据记录。

公开(公告)号：US07623129B2

公开(公告)日：2009-11-24

申请号：US11537588

申请日：2006-09-29

Applicant: Ellen Sagalov

Inventor： Ellen Sagalov

IPC: G06T11/20

CPC classification number: G06T11/206 ,  Y10S707/99945 ,  Y10S707/99948

Abstract: A computer readable storage medium includes executable instructions to associate two or more data sets with two or more vertices in a Venn graph. An intersection of the two or more data sets is associated with a vertex in the Venn graph. A plurality of outliers is associated between the two or more data sets and the intersection of the two or more data sets with a plurality of vertices disposed between the two or more vertices and the vertex in the Venn graph.

Abstract translation: 计算机可读存储介质包括可执行指令，以在维恩图中将两个或多个数据集与两个或多个顶点相关联。 两个或多个数据集的交集与维恩图中的顶点相关联。 多个异常值相关联在两个或多个数据集之间，并且两个或多个数据集与布置在两个或多个顶点之间的多个顶点和维恩图中的顶点相关联。

公开(公告)号：US12293320B2

公开(公告)日：2025-05-06

申请号：US17231057

申请日：2021-04-15

Applicant: BUSINESS OBJECTS SOFTWARE LTD.

Inventor： Jacques Doan Huu

IPC: G06F17/15 ,  G06F18/2433 ,  G06N20/00 ,  G06Q10/04 ,  G06Q10/0635 ,  G06Q10/067

Abstract: Provided is a system and method which can identify a causal relationship for anomalies in a time-series signal based on co-occurring and preceding anomalies in another time-series signal. In one example, the method may include identifying a recurring anomaly within a time-series signal of a first data value, determining a time-series signal of a second data value that is a cause of the recurring anomaly in the time-series signal of the first data value based on a preceding and co-occurring anomaly in the time-series signal of the second data value, and storing a correlation between the preceding and co-occurring anomaly in the time-series signal of the second data value and the recurring anomaly in the time-series signal of the first data value.

公开(公告)号：US12271797B2

公开(公告)日：2025-04-08

申请号：US17313460

申请日：2021-05-06

Applicant: BUSINESS OBJECTS SOFTWARE LTD.

Inventor： Louis Desreumaux ,  Jacques Doan Huu

IPC: G06N20/20 ,  G06N5/01

Abstract: Systems and methods include determination of a first plurality of sets of data, each including values associated with respective ones of a first plurality of features, partial training of a first machine-learning model based on the first plurality of sets of data, determination of one or more of the first plurality of features to remove based on the partially-trained first machine-learning model, removal of the one or more of the first plurality of features to generate a second plurality of sets of data, partial training of a second machine-learning model based on the second plurality of sets of data, determination that a performance of the partially-trained second machine-learning model is less than a threshold, addition, in response to the determination, of the one or more of the first plurality of features to the second plurality of sets of data, and training of the partially-trained first machine-learning model based on the first plurality of sets of data.

公开(公告)号：US20250053836A1

公开(公告)日：2025-02-13

申请号：US18931779

申请日：2024-10-30

Applicant: BUSINESS OBJECTS SOFTWARE LTD.

Inventor： Jacques DOAN HUU ,  Elouan ARGOUARCH

IPC: G06N5/04 ,  G06N20/00

Abstract: Provided are a system and method which iteratively predicts an output signal of a time-series data value via execution of a time-series machine learning model on input data, decomposes the predicted output signal into a plurality of component signals corresponding to a plurality of components of the time-series machine learning model, the plurality of component signals comprising a trend signal. a cyclic signal, and a fluctuation signal, determines a plurality of global values respectively corresponding to the plurality of component signals for a first subset of the predicted output signal, where a global value is determined based on an absolute value of a respective component signal within the first subset, constructs a plurality of bars respectively corresponding to global values of the plurality of component signals, and displays the plurality of bars via a user interface.

公开(公告)号：US12159240B2

公开(公告)日：2024-12-03

申请号：US17233600

申请日：2021-04-19

Applicant: BUSINESS OBJECTS SOFTWARE LTD.

Inventor： Jacques Doan Huu ,  Elouan Argouarch

IPC: G06N5/04 ,  G06N20/00

Abstract: Provided is a system and method which decomposes a predicted output signal of a time-series forecasting model into a plurality of sub signals that correspond to a plurality of components, and determines and displays a global contribution of each component. In one example, the method may include iteratively predicting an output signal of a time-series data value via execution of a time-series model, decomposing the predicted output signal into a plurality of component signals corresponding to a plurality of components of the time-series machine learning algorithm, respectively, and displaying the plurality of global values via a user interface.

公开(公告)号：US12087255B2

公开(公告)日：2024-09-10

申请号：US18075743

申请日：2022-12-06

Applicant: BUSINESS OBJECTS SOFTWARE LTD.

Inventor： Jean Christophe Cros

IPC: G09G5/38

CPC classification number: G09G5/38 ,  G09G2354/00

Abstract: An example method and system for display of out-of-window status indicators in a virtual shelf of a diagram window. A diagram framework displays a first portion of a diagram within a diagram window of a display device. The diagram comprises a set of shapes and a set of connectors representing a corresponding set of relationships between a set of objects. The framework detects that a first shape of the set of shapes at a first position of the first shape and a first status indicator associated with the first shape at a first position of the first status indicator are at least partially outside a first visible portion of the diagram within the diagram window. The diagram framework determines a second position of the first status indicator within the diagram window. The first status indicator at the second position of the first status indicator is displayed within the diagram window.

公开(公告)号：US12050628B1

公开(公告)日：2024-07-30

申请号：US18348143

申请日：2023-07-06

Applicant: Business Objects Software Ltd.

Inventor： Paul O'Hara ,  Ying Wu ,  Malte Christian Kaufmann

IPC: G06F16/28 ,  G06F16/23

CPC classification number: G06F16/285 ,  G06F16/2365

Abstract: Anomalies may be detected using a multiple machine learning model anomaly detection framework. A clustering model is trained using an unsupervised machine learning algorithm on a historical anomaly dataset. A plurality of clusters of records are determined by applying the historical anomaly dataset to the clustering model. Then it is determined whether each cluster of the plurality of clusters is an anomaly-type cluster or a normal-type cluster. The plurality of labels for the plurality of records are updated based on the particular record's cluster classification. Non-pure clusters are determined from among the plurality of clusters based on a purity threshold. A supervised machine learning model is trained for each of the non-pure clusters using the records in the given cluster and the labels for each of those records. Then, predictions of an anomaly are made using the clustering model and the supervised machine learning models.

公开(公告)号：US11914667B2

公开(公告)日：2024-02-27

申请号：US17669141

申请日：2022-02-10

Applicant: Business Objects Software Ltd.

Inventor： Shou-Chieh Chao ,  Sanam Narula ,  Nathan Wang ,  Walter Mak ,  Tsz Hong Sung

IPC: G06F40/103 ,  G06F16/957 ,  G06F16/22 ,  G06F16/904 ,  G06T11/20

CPC classification number: G06F16/9574 ,  G06F16/2237 ,  G06F16/2264 ,  G06F16/904 ,  G06F40/103 ,  G06T11/206

Abstract: Some embodiments provide a program. The program receives a visualization collection definition specifying a plurality of visualization definitions for a plurality of visualization definitions. Each visualization definition in the plurality of visualization definitions specifies a multi-dimensional array of data definition. The program further identifies a set of multi-dimensional array of data definitions specified in the plurality of visualization definitions of the visualization collection definition. The program also sends a request for the set of multi-dimensional array of data definitions to a computing system. The program further receives the set of multi-dimensional array of data definitions from the computing system. The program also stores the set of multi-dimensional array of data definitions in a cache storage of the mobile device for later use.