IP Library › Granted Patent US 12,639,374
Granted Patent B2
US 12,639,374 · App. 18/402,714 · Granted May 26, 2026

Content based related view recommendations

Inventors: Connie Hong-Ying Wong (Vancouver, CA); Xiangbo Mao (Vancouver, CA); Kazem Jahanbakhsh (Vancouver, CA); Eric Roy Brochu (Vancouver, CA)
Assignee: Tableau Software, LLC
G06F16/904G06F16/90332G06F16/9035G06F16/908G06F16/909G06N20/00
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Quick Facts
Patent No.
US 12,639,374
App. No.
18/402,714
Filed
Jan 2, 2024
Granted
May 26, 2026
Kind
B2
Art Unit
2198
USPC
707/722
Abstract

A method identifies related data visualizations. A computing device displays a data visualization according to a data source. The data visualization displays of one or more first data fields from the data source, and is displayed according to one or more first metadata fields. The device identifies a collection of predefined data visualizations for the data source. For each element in the collection, the device computes a respective ranking according to a plurality of influence scores, each influence score computed according to comparing data fields and metadata fields of the respective predefined data visualization to the one or more first data fields and the one or more associated first metadata fields. The device then selects a subset of the predefined data visualizations that have top ranking and provides an ordered list of the selected subset, including at least one influence score for each included data visualization.

Claims (39)

1 . A method for providing relevant related data visualizations, performed at a computing device having a display, one or more processors and memory storing one or more programs configured for execution by the one or more processors, the method comprising:

displaying a data visualization according to a data source, the data visualization including display of one or more first data fields from the data source, and displayed according to one or more associated first metadata fields;

identifying a collection of predefined data visualizations for the data source, where the collection of predefined data visualizations are stored in association with a selected organization;

for each predefined data visualization in the collection, computing a respective ranking according to a plurality of influence scores, each influence score is computed according to comparing data fields and metadata fields of the respective predefined data visualization to the one or more first data fields and the one or more associated first metadata fields and each influence score is computed using a recommendation model that uses natural language processing of text content included in the metadata fields of the respective predefined data visualizations, wherein the recommendation model is trained on metadata fields of the collection of predefined data visualizations that are stored in association with the selected organization and metadata fields of data visualization other than the collection of predefined data visualizations that are stored in association with the selected organization;

selecting a subset of the predefined data visualizations that have top ranking; and

providing a report that includes an ordered list of the selected subset of predefined data visualizations, including at least one influence score for each of the predefined data visualizations in the ordered list.

2 . The method of claim 1 , wherein computing the respective ranking comprises generating meta-attributes for the metadata fields by combining metadata field labels with their respective metadata field values, tokenizing the meta-attributes, sorting tokens of the meta-attributes, and rank ordering the tokens based on frequency of their occurrence.

3 . The method of claim 1 , wherein identifying the collection of predefined data visualizations comprises excluding one or more data visualizations associated with one or more metadata field values.

4 . The method of claim 1 , wherein identifying the collection of predefined data visualizations comprises excluding one or more data visualizations based on one or more missing metadata field values.

5 . The method of claim 1 , wherein identifying the collection of predefined data visualizations comprises excluding one or more data visualizations depending on the recommendation model.

6 . The method of claim 1 , wherein computing the respective ranking comprises mapping dominant topics to their associated metadata fields to evaluate an influence score of each metadata field.

7 . The method of claim 6 , wherein computing the respective ranking further comprises determining the dominant topics for the respective predefined data visualization based on values included in the metadata fields.

8 . The method of claim 1 , wherein each influence score is based on a count of a number of data visualizations that share a same value.

9 . The method of claim 1 , wherein providing the report comprises providing a narrative for a predefined data visualization based on its top ranked meta-data fields.

10 . A system for visualizing data:

one or more processors;

memory coupled to the one or more processors;

a display; and

one or more programs stored in the memory and configured for execution by the one or more processors, the one or more programs comprising instructions for:

displaying a data visualization according to a data source, the data visualization including display of one or more first data fields from the data source, and displayed according to one or more associated first metadata fields;

identifying a collection of predefined data visualizations for the data source, where the collection of predefined data visualizations are stored in association with a selected organization;

for each predefined data visualization in the collection, computing a respective ranking according to a plurality of influence scores, each influence score is computed according to comparing data fields and metadata fields of the respective predefined data visualization to the one or more first data fields and the one or more associated first metadata fields and each influence score is computed using a recommendation model that uses natural language processing of text content included in the metadata fields of the respective predefined data visualizations, wherein the recommendation model is trained on metadata fields of the collection of predefined data visualizations that are stored in association with the selected organization and metadata fields of data visualization other than the collection of predefined data visualizations that are stored in association with the selected organization;

selecting a subset of the predefined data visualizations that have top ranking; and

providing a report that includes an ordered list of the selected subset of predefined data visualizations, including at least one influence score for each of the predefined data visualizations in the ordered list.

11 . The system of claim 10 , wherein computing the respective ranking comprises generating meta-attributes for the metadata fields by combining metadata field labels with their respective metadata field values, tokenizing the meta-attributes, sorting tokens of the meta-attributes, and rank ordering the tokens based on frequency of their occurrence.

12 . The system of claim 10 , wherein identifying the collection of predefined data visualizations comprises excluding one or more data visualizations associated with one or more metadata field values.

13 . The system of claim 10 , wherein identifying the collection of predefined data visualizations comprises excluding one or more data visualizations based on one or more missing metadata field values.

14 . The system of claim 10 , wherein identifying the collection of predefined data visualizations comprises excluding one or more visualizations depending on the recommendation model.

15 . The system of claim 10 , wherein computing the respective ranking comprises mapping dominant topics to their associated metadata fields to evaluate an influence score of each metadata field.

16 . The system of claim 15 , wherein computing the respective ranking further comprises determining the dominant topics for the respective predefined data visualization based on values included in the metadata fields.

17 . The system of claim 10 , wherein each influence score is based on a count of a number of data visualizations that share a same value.

18 . The system of claim 10 , wherein providing the report comprises providing a narrative for a predefined data visualization based on its top ranked meta-data fields.

19 . A non-transitory computer readable storage medium storing one or more programs, the one or more programs configured for execution by a computing device having one or more processors, memory, and a display, the one or more programs comprising instructions for:

displaying a data visualization according to a data source, the data visualization including display of one or more first data fields from the data source, and displayed according to one or more associated first metadata fields;

identifying a collection of predefined data visualizations for the data source, where the collection of predefined data visualizations are stored in association with a selected organization;

for each predefined data visualization in the collection, computing a respective ranking according to a plurality of influence scores, each influence score is computed according to comparing data fields and metadata fields of the respective predefined data visualization to the one or more first data fields and the one or more associated first metadata fields and each influence score is computed using a recommendation model that uses natural language processing of text content included in the metadata fields of the respective predefined data visualizations, wherein the recommendation model is trained on metadata fields of the collection of predefined data visualizations that are stored in association with the selected organization and metadata fields of data visualization other than the collection of predefined data visualizations that are stored in association with the selected organization;

selecting a subset of the predefined data visualizations that have top ranking; and

providing a report that includes an ordered list of the selected subset of predefined data visualizations, including at least one influence score for each of the predefined data visualizations in the ordered list.

20 . The non-transitory computer readable storage medium of claim 19 , wherein computing the respective ranking comprises generating meta-attributes for the metadata fields by combining metadata field labels with their respective metadata field values, tokenizing the meta-attributes, sorting tokens of the meta-attributes, and rank ordering the tokens based on frequency of their occurrence.

Continuity (2)
Continuation 17158911 · Jan 26, 2021
Related Publication 20240134914A1 · Apr 25, 2024
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