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US 2020/0005181 A1Published application
Vector generation for distributed data sets
AssigneePalanir Technologies Inc.
InventorsRahul Agarwal, Daniel Erenrich
Life of this patent
Estimating the term…
Abstract
In various example embodiments, a vector modeling system is configured to access a set of data distributed across client devices and stored in a structured format. The vector modeling system determines vector parameters and vector templates suitable for the set of data and transforms the set of data from the structured format into a second format including one or more vectors based on one or more transformation strategies. The vector modeling system stores the transformed data and performs machine learning analysis on the vector.
Claims21
(canceled)
A method, comprising:
- distributing, from a server, an integrated vector template to a first client device and a second client device, the integrated vector template being generated by the server based on a first set of data provided by the first client device and a second set of data provided by the second client device, the first and second sets of data being configured in a first format;
- sending, from the server to the first client device, a first conversion instruction that causes the first client device to generate the first set of data in a second format based on the integrated vector template, the first set of data in the second format comprising a first set of vectors that have one or more vector values converted from one or more data entries in the first set of data;
- receiving, at the server, a first converted set of data from the first client device, the first converted set of data comprising the first set of data in the second format;
- sending, from the server to the second client device, a second conversion instruction that causes the second client device to generate the second set of data in the second format based on the integrated vector template, the second set of data in the second format comprising a second set of vectors that have one or more vector values converted from one or more data entries in the second set of data;
- receiving, at the server, a second converted set of data from the second client device, the second converted set of data comprising the second set of data in the second format;
- mapping, by the server, each data entry in the first and second converted sets of data to a vector value to generate a conversion map, the conversion map assisting in transforming data entries, from the first or second client devices, to vector values that have a format compatible for processing by at least one machine learning algorithm;
- generating, by the server, at least one subsequent vector from an additional set of data using the conversion map;
- and
- processing, by the server, the at least one subsequent vector using the at least one machine learning algorithm.
6 more elements
A computer implemented system, comprising:
- one or more processors;
- a non-transitory machine-readable storage medium including instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
- distributing an integrated vector template to a first client device and a second client device, the integrated vector template being generated by the computer implemented system based on a first set of data provided by the first client device and a second set of data provided by the second client device, the first and second sets of data being configured in a first format;
- sending, to the first client device, a first conversion instruction that causes the first client device to generate the first set of data in a second format based on the integrated vector template, the first set of data in the second format comprising a first set of vectors that have one or more vector values converted from one or more data entries in the first set of data;
- receiving a first converted set of data from the first client device, the first converted set of data comprising the first set of data in the second format;
- sending, to the second client device, a second conversion instruction that causes the second client device to generate the second set of data in the second format based on the integrated vector template, the second set of data in the second format comprising a second set of vectors that have one or more vector values converted from one or more data entries in the second set of data;
- receiving a second converted set of data from the second client device, the second converted set of data comprising the second set of data in the second format;
- mapping each data entry in the first and second converted sets of data to a vector value to generate a conversion map, the conversion map assisting in transforming data entries, from the first or second client devices, to vector values that have a format compatible for processing by at least one machine learning algorithm;
- generating at least one subsequent vector from an additional set of data using the conversion map;
- and
- processing the at least one subsequent vector using the at least one machine learning algorithm.
8 more elements
A non-transitory machine-readable storage medium including instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising:
- distributing an integrated vector template to a first client device and a second client device, the integrated vector template being generated by the machine based on a first set of data provided by the first client device and a second set of data provided by the second client device, the first and second sets of data being configured in a first format;
- sending, to the first client device, a first conversion instruction that causes the first client device to generate the first set of data in a second format based on the integrated vector template, the first set of data in the second format comprising a first set of vectors that have one or more vector values converted from one or more data entries in the first set of data;
- receiving a first converted set of data from the first client device, the first converted set of data comprising the first set of data in the second format;
- sending, to the second client device, a second conversion instruction that causes the second client device to generate the second set of data in the second format based on the integrated vector template, the second set of data in the second format comprising a second set of vectors that have one or more vector values converted from one or more data entries in the second set of data;
- receiving a second converted set of data from the second client device, the second converted set of data comprising the second set of data in the second format;
- mapping each data entry in the first and second converted sets of data to a vector value to generate a conversion map, the conversion map assisting in transforming data entries, from the first or second client devices, to vector values that have a format compatible for processing by at least one machine learning algorithm;
- generating at least one subsequent vector from an additional set of data using the conversion map;
- and
- processing the at least one subsequent vector using the at least one machine learning algorithm.
6 more elements
Dependencies are inferred from the claim text.