PATENT CLAIM ANALYSIS

Application Number: 16379470
Application Type: Utility
Filing Date: 2019-04
Publication Date: 2019-10
Patent Classification: ["707", "738000"]

Abstract:
A hierarchical structure (e.g., a hierarchy) for use in hierarchical analysis (e.g., hierarchical forecasting) of timestamped data can be automatically generated. This automated approach to determining a hierarchical structure involves identifying attributes of the timestamped data, clustering the timestamped data to select attributes for the hierarchy, ordering the attributes to achieve a recommended hierarchical order, and optionally modifying the hierarchical order based on user input. Through the approach disclosed herein, a hierarchy can be generated that is designed to perform well under hierarchical models. This recommended hierarchy for use in hierarchical analysis may be agnostic to any planned hierarchy provided by or used by a user to otherwise interpret the timestamped data.

Claim (Index 21):
A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause a data processing apparatus to perform operations including:\n receiving timestamped data, wherein the timestamped data is associated with a set of attributes and a set of independent variables, wherein the set of attributes comprises one or more time-independent attributes, and wherein the set of independent variables comprises one or more independent variables; clustering the timestamped data into a set of clusters, wherein clustering the timestamped data comprises detecting patterns in the timestamped data, determining responses of the timestamped data to the set of independent variables, and generating cluster results based on the patterns of the timestamped data and the responses of the timestamped data to the set of independent variables; selecting attributes from the set of attributes using the set of clusters, wherein selecting the attributes comprises identifying, from the set of attributes, a subset of attributes that are associated with the clusters; ordering the selected attributes, wherein ordering the selected attributes comprises sequentially building an order of the selected attributes or globally building the order of the selected attributes; wherein sequentially building the order of the selected attributes comprises sequentially determining a location for a given attribute of the selected attributes in a current arrangement, updating the current arrangement with the location for the given attribute, and determining a location for a next attribute of the selected attributes in the updated current arrangement; and wherein globally building the order of the selected attributes comprises determining a first order of the selected attributes, determining a second order of the selected attributes, and comparing the first order and the second order to generate the order of the selected attribute; generating a structure for a hierarchy using the order of the selected attributes, wherein the structure for the hierarchy defines a plurality of levels of the hierarchy; and generating predicted values across the plurality of levels of the hierarchy using the received timestamped data and the generated hierarchical structure, wherein predicted values of one or more levels of the plurality of levels is informed by predicted values of another level of the plurality of levels.

Metadata:
- Claim Count in Document: 18.0
- Percentile: 100.0
- Lexical Diversity: 1.96875
- Patent Class: 707.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['16193661', '15927610', '16233302', '15922317', '15087148']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1879745033178666
- 35 USC 102 Novelty (BERT): 0.4880663730113151
- Combined Prediction Score: 0.2179836902872114
- Mean Citation Score: 191.354548
- Max Citation Score: 208.3085
- Similarity Product: 156.03772024378182

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test