Dataset browsing using additive filters

• US 10,528,569 B2
• Filed: 06/26/2014
• Issued: 01/07/2020
• Est. Priority Date: 06/26/2014
• Status: Active Grant

• Current Assignee: Hewlett Packard Enterprise Development LP (Hewlett-Packard Enterprise Company)
• Original Assignee: Hewlett Packard Enterprise Development LP (Hewlett-Packard Enterprise Company)
• Inventors: Hailpern, Joshua
• Primary Examiner(s): Andersen, Kristopher
• Application Number:
  US15/316,857
• Publication Number:
  US 20170140002A1
• Time in Patent Office: 2,021 Days
• CPC Class Codes: G06F 16/24573 using data annotations, e.g. user-defined metadata
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/285 Clustering or classification

Abstract

Examples relate to dataset browsing using additive filters. In some examples, metadata associated with a user-related dataset is processed to obtain explicit information that describes attributes for each data record in the user-related dataset. Further, a semantic analysis of content of the user-related dataset is performed to identify topics. At this stage, the explicit information and the topics are used to generate contextual cues. A dataset display for the user-related dataset is displayed, where the dataset display is empty prior to selection of any of the contextual cues. In response to a selection of a first cue, a dataset display of the user-related dataset is updated to show data records that are associated with the first cue. In response to a selection of a second cue, the dataset display is updated to show data records that are associated with the first cue and the second cue.

Claims

1. A method for dataset browsing using additive filters, the method comprising:

processing metadata associated with a user-related dataset to obtain explicit information that describes a plurality of attributes for each data record in the user-related dataset;

performing a semantic analysis of content of the user-related dataset to identify a plurality of topics;

using the explicit information and the plurality of topics to generate a plurality of contextual cues;

display a dataset display for the user-related dataset, wherein the dataset display is empty prior to selection of any of the plurality of contextual cues;

in response to a selection of a first cue of the plurality of contextual cues, updating the dataset display of the user-related dataset to show data records that are associated with the first cue; and

in response to a selection of a second cue of the plurality of contextual cues, updating the dataset display to show data records that are associated with the first cue and the second cue.

2. The method of claim 1, wherein the user-related dataset is personal data related to a user, and wherein the explicit information describes characteristics of the user.

3. The method of claim 1, wherein the plurality of contextual cues are generated further using inherent information that describes characteristics of a user application for providing access to the data set.

4. The method of claim 1, further comprising:

simultaneously displaying a cue subset of the plurality of contextual cues, wherein cues of the cue subset are determined to have a higher probability of being relevant to a user; and

in response to the selection of the first cue, updating a cue display of the cue subset to show cues that are related to the first cue.

5. The method of claim 1, further comprising:

in response to a deselection of the first cue, updating the dataset display to show data records that are associated with the second cue.

6. A system for dataset browsing using additive filters, the system comprising:

a storage device to store a user-related dataset; and

a processor to;

process metadata associated with a user-related dataset to obtain explicit information that describes a plurality of attributes for each data record in the user-related dataset;

perform a semantic analysis of content of the user-related dataset to identify a plurality of topics;

use the explicit information and the plurality of topics to generate a plurality of contextual cues;

display a dataset display for the user-related dataset, wherein the dataset display is empty prior to selection of any of the plurality of contextual cues;

in response to a selection of a first cue of the plurality of contextual cues, update the dataset display of the user-related dataset to show data records that are associated with the first cue; and

in response to a selection of a second cue of the plurality of contextual cues, update the dataset display to show data records that are associated with the first cue and the second cue.

7. The system of claim 6, wherein the dataset display is empty prior to the selection of the first cue.

8. The system of claim 6, wherein the user-related dataset is personal data related to a user, and wherein the explicit information describes characteristics of the user.

9. The system of claim 6, wherein the plurality of contextual cues are generated further using inherent information that describes characteristics of a user application for providing access to the data set.

10. The system of claim 6, wherein the processor is further to:

simultaneously display a cue subset of the plurality of contextual cues, wherein cues of the cue subset are determined to have a higher probability of being relevant to a user; and

in response to the selection of the first cue, update a cue display of the cue subset to show cues that are related to the first cue.

11. The system of claim 6, wherein the processor is further to:

in response to a deselection of the first cue, update the dataset display to show data records that are associated with the second cue.

12. A non-transitory machine-readable storage medium encoded with instructions executable by a processor for dataset browsing using additive filters, the machine-readable storage medium comprising instructions to:

process metadata associated with a user-related dataset to obtain explicit information that describes a plurality of attributes for each data record in the user-related dataset;

perform a semantic analysis of content of the user-related dataset to identify a plurality of topics;

use the explicit information and the plurality of topics to generate a plurality of contextual cues;

simultaneously display a cue subset of the plurality of contextual cues and a dataset display of the user-related data, wherein cues of the cue subset are determined to have a higher probability of being relevant to a user, and wherein the dataset display is empty prior to selection of any of the plurality of contextual cues;

in response to a selection of a first cue of the plurality of contextual cues, update the dataset display of the user-related dataset to show data records that are associated with the first cue; and

in response to a selection of a second cue of the plurality of contextual cues, update the dataset display to show data records that are associated with the first cue and the second cue.

13. The non-transitory machine-readable storage medium of claim 12, wherein the user-related dataset is personal data related to a user, and wherein the explicit information describes characteristics of the user.

14. The non-transitory machine-readable storage medium of claim 12, wherein the plurality of contextual cues are generated further using inherent information that describes characteristics of a user application for providing access to the data set.

15. The non-transitory machine-readable storage medium of claim 12, wherein the processor is further to:

in response to the selection of the first cue, update a cue display of the cue subset to show cues that are related to the first cue.