Method for managing a machine learning model
US-2020104754-A1 · Apr 2, 2020 · US
US11048868B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11048868-B2 |
| Application number | US-201916396118-A |
| Country | US |
| Kind code | B2 |
| Filing date | Apr 26, 2019 |
| Priority date | Apr 26, 2019 |
| Publication date | Jun 29, 2021 |
| Grant date | Jun 29, 2021 |
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A data narration generating system generates snippets that include representations of data in one of a plurality of formats for inclusion into a data narration. The narration generating system receives selected data to be included into the data narration and provides the selected data to a plurality of ML models. The plurality of ML models are trained in generating snippets in one of the plurality of formats which can include textual format and a tabular format. Snippets in graphical formats can also be generated by rule-based processes. A plurality of snippets are thus generated in one or more of the plurality of formats which can then be presented to a user for selection and inclusion into the data narration. Alternately, a subset of the plurality of snippets can also be selected automatically based on a quality and quantity of data and a voting mechanism. The data narration thus generated is further configured to present different views based on privileges associated with user profiles.
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What is claimed is: 1. An Artificial Intelligence (AI) based data narration generating system comprising: at least one processor; a non-transitory computer readable medium storing machine-readable instructions that cause the at least one processor to: access one or more data sources to be used for generating a narration, wherein the narration includes a presentation of data from the one or more data sources in one or more of a plurality of formats; select columns from the data that are to be included in the narration from the data sources based on an input from an administrative user; provide the data to a plurality of machine learning (ML) models trained in generation of one or more snippets, wherein each snippet includes a presentation of at least a subset of the data in one of the plurality of formats; determine based at least on corresponding data types of each of the columns, summarization and aggregation attributes of data in the columns; enable generation of a plurality of the snippets by at least a subset of the plurality ML models in one or more formats of the plurality of formats that correspond to the subset of ML models generating the snippets; automatically select at least a subset of the plurality of the snippets via a voting process for presentation to the administrative user, wherein the automatic selection is based at least on quality of data including the summarization and the aggregation attributes of the data in the columns; enable presentation of the selected subset of snippets to the administrative user via an input/output graphical user interface (GUI); receive selection of one or more snippets by the administrative user from the subset of snippets; and generate the narration including the user selected snippets arranged in accordance with an order as received from the administrative user. 2. The narration generating system of claim 1 , further comprising instructions that cause the processor to: access training data for training the plurality of ML models in generating the snippets, wherein the training data includes different data sets and corresponding snippets that present the data sets in a preferred one of the plurality of formats. 3. The narration generating system of claim 1 , further comprising instructions that cause the processor to: enable the administrative user to provide access to the data narration to one or more end users based on privileges mapped to profiles of the end users. 4. The narration generating system of claim 3 , wherein the instructions for enabling the administrative user to provide access to the narration to one or more end users further comprising instructions that cause the processor to: provide access to views of the data narration to the end users, wherein the views provided to the end users include corresponding portions of the data that the end users are permitted to view based on the privileges. 5. The narration generating system of claim 1 , further comprising instructions that cause the processor to: collect feedback from the administrative user and end users for the narration. 6. The narration generating system of claim 1 , wherein the plurality of formats include a textual format, a data structure format and a graphical format. 7. The narration generating system of claim 6 , wherein the instructions for automatically selecting at least a subset of the plurality of the snippets further comprising instructions that cause the processor to: enable generation of at least one of the plurality of the snippets by each of the plurality ML models in one of the plurality of formats. 8. The narration generating system of claim 7 , wherein the instructions for automatically selecting at least the subset of the plurality of the snippets further comprising instructions that cause the processor to: automatically select the subset of the plurality of the snippets based on quality of the data, volume of the data and the voting process based on user feedback. 9. The narration generating system of claim 1 , wherein a textual format includes a natural language summary obtained from the data that is to be included in a corresponding snippet. 10. The narration generating system of claim 1 , wherein the plurality of ML models include recurrent neural network (RNN), Key Press Markup Language (KPML) and simplenlg. 11. A method of generating data narrations, comprising: selecting data that is to be included in a data narration from one or more data sources, the selection of data is based on an input from an administrative user and the data narration includes a presentation of data from the one or more data sources in one or more of a plurality of formats; providing the data to a plurality of machine learning (ML) models trained in generation of a plurality of snippets, wherein each snippet includes a presentation of at least a subset of the data in one of the plurality of formats; determining, by each of the plurality of ML models, a subset of the data to be included in the snippets and one of the plurality of formats of presenting the subset of the data in the snippets; determining based at least on corresponding data types of each of the columns, summarization and aggregation attributes of data in the columns; enabling generation of each of the plurality of the snippets by at least one ML model of the plurality ML models in a format of the plurality of formats that correspond to the ML model generating the snippet; automatically selecting at least a subset of the plurality of snippets for presentation to the administrative user via an input/output graphical user interface (I/O GUI), the automatic selection based on a quality of the data, quantity of the data and a voting mechanism wherein the quality of data includes the summarization and the aggregation attributes of the data in the columns; receiving selection of one or more of the subset of snippets by the administrative user via the output GUI; generating the data narration including the user selected snippets arranged in accordance with an order as received from the administrative user; and enabling access to the narration to a plurality of end users based on respective user profiles of the end users, wherein the user profiles determine one or more of the user selected snippets that are displayed to each of the end users in the data narration. 12. The method of claim 11 , further comprising: including, within the data narration, the voting mechanism that enables the end users to provide feedback to the data narration. 13. The method of claim 11 , wherein automatically selecting at least the subset of the plurality of snippets further comprising: automatically selecting at least a subset of the plurality of snippets based on historical feedback received from the end users to prior narrations. 14. The method of claim 11 , wherein automatically selecting at least the subset of the plurality of snippets further comprising: accessing configuration input from the administrative user regarding a number of snippets to be automatically selected; and selecting, based on the configuration input, a highest scoring snippet of the plurality of snippets for presentation via the output GUI. 15. The method of claim 11 , wherein receiving the selection of the subset of snippets further comprising: receiving, via drag-and-drop operations, selection of one or more of the subset of snippets by the administrative user via the output GUI. 16. The method of claim 11 , further comprising: enabling, the administrative user to edit the data to be included in the narration.
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characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU] · CPC title
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