Context-based search and relevancy generation

Patent metadata

Field	Value
Publication number	US-9922098-B2
Application number	US-201514814038-A
Country	US
Kind code	B2
Filing date	Jul 30, 2015
Priority date	Nov 6, 2014
Publication date	Mar 20, 2018
Grant date	Mar 20, 2018

Abstract

A computing device receives a trigger to surface relevant content. The device also obtains a variety of different types of cross-source contextual information. Items of content are identified and relevancy weights are obtained based on the contextual information. A relevancy is calculated, based on the relevancy weights, for each item of content. The items of content are surfaced.

First claim

What is claimed is:

1. A computing system, comprising:
at least one processor; and
memory storing instructions executable by the at least one processor, wherein the instructions, when executed, configure the computing system to provide:
a context identification system configured to detect a plurality of different sensor inputs, indicative of a plurality of different items of context, from a plurality of different sources of context;
a cross-source search component configured to detect a trigger input and search a plurality of different content sources, to identify a set of documents, based on the trigger input;
a relevancy generator configured to generate a relevancy metric corresponding to each document in the identified set of documents, based on the plurality of different items of context; and
a user interface component configured to generate a user interface display that selectively displays the documents in the set of documents based on the corresponding relevancy metric.

2. The computing system of claim 1 wherein the context identification system is configured to detect whether a user is using the computing system in a work context or a non-work context, and the relevancy generator is configured to generate the relevancy metric for the documents based on the detected work context or non-work context.

3. The computing system of claim 2 wherein the context identification system comprises:
a location detector configured to detect a user location,
wherein the relevancy generator is configured to generate the relevancy metric for the documents based on the detected user location.

4. The computing system of claim 2 wherein the context identification system comprises:
a usage pattern identifier configured to identify temporal document usage patterns corresponding to the documents, each temporal document usage pattern being indicative of a pattern of usage of a corresponding document, by the user, over time, and
wherein the relevancy generator is configured to generate the relevancy metric for the documents based on the identified temporal document usage patterns corresponding to each document.

5. The computing system of claim 2 wherein the context identification system comprises:
a document interaction detector configured to detect user interactions corresponding to each of the documents, and
wherein the relevancy generator is configured to generate the relevancy metric for the documents based on the detected user interactions.

6. The computing system of claim 5 wherein the document interaction detector is configured to detect recency of user interactions, and wherein the relevancy generator is configured to generate the relevancy metric based on the detected recency.

7. The computing system of claim 5 wherein the document interaction detector is configured to detect interaction type, and wherein the relevancy generator is configured to generate the relevancy metric based on the detected interaction type.

8. The computing system of claim 5 wherein the document interaction detector is configured to detect frequency of interaction, and wherein the relevancy generator is configured to generate the relevancy metric based on the detected frequency of interaction.

9. The computing system of claim 2 wherein the context identification system comprises:
a calendar detector configured to access a calendar system and identify user interactions with the documents relative to calendar items of the user,
wherein the relevancy generator is configured to generate the relevancy metric for the documents based on the identified user interactions with the documents relative to the calendar items.

10. The computing system of claim 9 wherein the calendar detector is configured to identify whether the user is interacting with the documents in temporal proximity to meetings or deadlines.

11. The computing system of claim 2 wherein the context identification system comprises:
a document personnel detector configured to detect other personnel that are related to the documents, other than the user,
wherein the relevancy generator is configured to generate the relevancy metric for the documents based on the detected other personnel.

12. The computing system of claim 11 wherein the context identification system comprises:
a proximity detector configured to detect a proximity of the user to the other personnel,
wherein the relevancy generator is configured to generate the relevancy metric based on the detected proximity to the other personnel.

13. The computing system of claim 2 wherein the context identification system comprises:
a device type detector configured to detect a type of user device being used by the user,
wherein the relevancy generator is configured to generate the relevancy metric for the documents based on the detected type of user device.

14. The computing system of claim 13 wherein the context identification system comprises:
an open application detector configured to detect open applications on the user device,
wherein the relevancy generator is configured to generate the relevancy metric for the documents based on the detected open applications.

15. The computing system of claim 2 wherein the context identification system comprises:
a biometric data detector configured to detect biometric data corresponding to the user,
wherein the relevancy generator is configured to generate the relevancy metric for the documents based on the biometric data.

16. The computing system of claim 2 wherein the relevancy generator is configured to generate a confidence score associated with each of the documents, and wherein the instructions, when executed, configure the computing system to provide:
a dialog engine,
wherein the relevancy generator is configured to engage the dialog engine to obtain additional context information from the user when one or more confidence scores fall below a threshold value.

17. The computing system of claim 2 wherein the relevancy generator is configured to generate the relevancy metric for the documents based on weighted relevancy criteria, and wherein the relevancy generator is configured to vary weights on the weighted relevancy criteria based on the items of context.

18. A computer implemented method, comprising:
detecting a plurality of different sensor inputs, indicative of a plurality of different items of context, from a plurality of different sources of context;
detecting a trigger input;
in response to the trigger input, searching a plurality of different content sources, to identify a set of documents, based on the trigger input;
detecting a user location;
generating a relevancy measure corresponding to each document in the identified set of documents, based on the user location and the plurality of different items of context; and
generating a user interface display that selectively displays the documents in the set of documents based on the corresponding relevancy score.

19. The computer implemented method of claim 18 wherein detecting a plurality of different sensor inputs comprises:
detecting a usage pattern sensor input that identifies temporal document usage patterns corresponding to the documents, each temporal document usage pattern being indicative of a pattern of usage of a corresponding document, by the user, over time, wherein generating a relevancy metric includes generating the relevancy metric for the documents based on the identified temporal document usage patterns corresponding to each document.

20. A computing system, c

Assignees

• Microsoft Technology Licensing Llc

Inventors

• Vogel Matthew
• Seto Julie C
• Stepanich Darron
• Kikin-Gil Erez

Classifications

• G06F17/30029

  Physics · mapped topic

• H04L61/609

  Electricity · mapped topic

• G06F17/30554 Primary

  Physics · mapped topic

• G06F3/0484

  for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range · CPC title

• G06F17/3053

  Physics · mapped topic