公开(公告)号：US20230010992A1

公开(公告)日：2023-01-12

申请号：US17367882

申请日：2021-07-06

Applicant: BUSINESS OBJECTS SOFTWARE LTD.

Inventor： Paul O'HARA ,  Malte Christian KAUFMANN ,  Alan McSHANE ,  Anirban BANERJEE ,  Mark AHERN

IPC: G06F16/2458 ,  G06F16/28 ,  G06F16/2457

Abstract: Systems and methods include determination, for each of a plurality of discrete features, of statistics based on a number of occurrences of each discrete value of the discrete feature in the data, determination of first summary statistics based on the determined statistics, determine of a dissimilarity for each discrete feature based on the first summary statistics and on the statistics determined for the discrete feature, determination of candidate discrete features based on the determined dissimilarities, determination, for each of the candidate discrete features, of second summary statistics based on values of a continuous feature associated with each discrete value of the candidate discrete feature, determination of a deviation score for each of the candidate discrete features based on the second summary statistics, and transmission of the candidate discrete features for display in association with the continuous feature based on the determined deviation scores.

公开(公告)号：US20220374765A1

公开(公告)日：2022-11-24

申请号：US17328427

申请日：2021-05-24

Applicant: BUSINESS OBJECTS SOFTWARE LTD.

Inventor： Ying WU ,  Jiazheng LI ,  Paul O'HARA ,  Malte Christian KAUFMANN

IPC: G06N20/00 ,  G06F16/2457

Abstract: Systems and methods include reception of a set of data, the set of data comprising a plurality of features, building, for each of a plurality of subsets of the plurality of features, a dimension reduction model based on the subset of features and associated values of the set of data, and, for each dimension reduction model, determination of a weight associated with each of subset of features based on the dimension model, identification of a predetermined number of features associated with the highest weights, and generation, for each dimension reduction model, of a data structure comprising the predetermined number of features and the weight associated with each of the predetermined number of features. A plurality of top features are determined based on the plurality of data structures, and a supervised learning model is trained based on the plurality of top features of the set of data.

公开(公告)号：US20220398246A1

公开(公告)日：2022-12-15

申请号：US17342812

申请日：2021-06-09

Applicant: BUSINESS OBJECTS SOFTWARE LTD.

Inventor： Paul O'HARA ,  Malte Christian KAUFMANN ,  Anirban BANERJEE ,  Ian DENVER ,  Alan McSHANE

IPC: G06F16/2458 ,  G06F16/28

Abstract: Systems and methods include determination, determine, for each of a plurality of discrete features, of statistics for each discrete value of the discrete feature based on values of a continuous feature associated with the discrete value, determination, for each discrete feature, of first summary statistics based on the statistics determined for each discrete value of the discrete feature, determination, for each discrete feature, of a dissimilarity based on the first summary statistics determined for the discrete feature and on the statistics determined for each discrete value of the discrete feature, determination of candidate discrete features of the discrete features based on the determined dissimilarities, the candidate discrete features comprising less than all of the discrete features, determination, for each of the candidate discrete features, of second summary statistics based on values of the continuous feature associated with each discrete value of the candidate discrete feature, determine of a deviation score for each of the candidate discrete features based on the second summary statistics, and presentation of the candidate discrete features based on the determined deviation scores.

公开(公告)号：US20220374450A1

公开(公告)日：2022-11-24

申请号：US17324667

申请日：2021-05-19

Applicant: BUSINESS OBJECTS SOFTWARE LTD.

Inventor： Paul O'HARA ,  Ying WU ,  Jiazheng LI ,  Cathal McGOVERN ,  Malte Christian KAUFMANN ,  Esther Rodrigo ORTIZ ,  Kerry O'CONNOR ,  Michael GOLDEN ,  Satinder SINGH

IPC: G06F16/26 ,  G06F16/2458

Abstract: Systems and methods include reception of a set of data including continuous features and a discrete feature, each continuous feature associated with a plurality of values and the discrete feature associated with a plurality of discrete values, determine, for each continuous feature, a relationship factor representing a relationship between the discrete feature and the continuous feature based on the plurality of values associated with the continuous feature and the plurality of discrete values, identify one of the continuous features associated with a largest one of the determined relationship factors, generate, for each of the other features, a correlation factor representing a correlation between the continuous feature and the identified continuous feature, determine, for each of the continuous features other than the identified continuous feature, a composite relationship score based on the relationship factor and the correlation factor associated with the feature, and present a visualization associated with the discrete feature, the identified continuous feature, and a continuous feature associated with a largest composite relationship score.

公开(公告)号：US20220357920A1

公开(公告)日：2022-11-10

申请号：US17313359

申请日：2021-05-06

Applicant: BUSINESS OBJECTS SOFTWARE LTD.

Inventor： Paul O'HARA ,  Malte Christian KAUFMANN

IPC: G06F7/535

Abstract: Systems and methods include reception of data including a plurality of continuous features and a first discrete feature, each of the plurality of continuous features associated with a plurality of values and the first discrete feature associated with a plurality of discrete values, determination of an overall output value of a function based on the plurality of values associated with each of the plurality of continuous features, determination, for each discrete value of the plurality of discrete values, of an output value of the function based on ones of the plurality of values associated with the discrete value, scaling of the output value determined for each discrete value based on the determined output values and the overall output value, and presentation of the scaled output values.