Automated supplementation of data model

• US 10,031,939 B2
• Filed: 09/30/2014
• Issued: 07/24/2018
• Est. Priority Date: 09/30/2014
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Rezaei, Pedram Faghihi, Netz, Amir M., Wilson, Adam D., Hays, Christopher A., Baumgartner, Patrick J.
• Primary Examiner(s): KUDDUS, DANIEL A
• Application Number:
  US14/502,687
• Publication Number:
  US 20160092603A1
• Time in Patent Office: 1,393 Days
• CPC Class Codes: G06F 16/24522 Translation of natural language queries to structured queries
• CPC Class Codes: G06F 16/907 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually

Abstract

Mechanisms to help a computing system respond to a request for information within a data model. After determining that there is insufficient information within the data model to respond to the request, the computing system identifies one or more additional data sources that are external to the data model and that contain information suitable to respond to the request. The computing system then automatically supplements the data model with at least one of such additional data sources. The computing system then responds to the request using the supplemented data model. In some embodiments, the supplementation is performed in advance of the request by analyzing the characteristics of the data model and/or by anticipating possible future requests. Thus, a data model grows automatically in response to particular usage of that data model to satisfy requests.

Claims

1. A method, implemented at a computing system that includes one or more hardware processors, for responding to a request for information associated with a data model that includes a plurality of data objects that are each associated with one of a plurality of data types, and a plurality of relationship types that define relationships between data types, the method comprising:

receiving a request for data from the data model that includes a first data object and a second data object;

in response to receiving the request,

determining that the first data object corresponds to a first data type; and

determining that the second data object does not correspond to any data type known by the data model; and

in response to determining that the second data object does not correspond to any data type known by the data model,

correlating the second data object to a second data type;

determining a relationship type between the first data type and the second data type;

based on the second data type or the determined relationship type, identifying an additional data source that includes data associated with the second data type;

generating a supplemented data model that comprises the data model and the additional data source;

determining a supplementation time period comprising a time period during which the additional data source supplements the data model; and

responding to the request within the supplementation time period using the supplemented data model.

2. The method in accordance with claim 1, the method further comprising determining that a controlling value of the request is not referenced in the data model, wherein determining that the data model does not include the information required to respond to the request is performed in response to determining that the controlling value of the request is not referenced in the data model.

3. The method in accordance with claim 2, wherein identifying one or more additional data sources comprises:

an act of identifying a data source that defines a data type of the controlling value that is not referenced in the data model.

4. The method in accordance with claim 3, wherein supplementing the data model comprises:

augmenting the data model with the identified data source.

5. The method in accordance with claim 4, wherein supplementing the data model further comprises:

finding relationship data between the data type of the controlling value and the data model; and

incorporating the relationship data into the data model.

6. The method in accordance with claim 1, wherein identifying an additional data source comprises:

applying at least one filter to determine that the additional data source includes the information.

7. The method in accordance with claim 6, the filter comprising a security filter that applies one or more security criteria.

8. The method in accordance with claim 6, the filter comprising a regional filter that applies one or more region-specific criteria.

9. The method in accordance with claim 6, wherein the filter comprises a performance filter that is based on one or more previous recordings of performance when supplementing the data model with the additional data source.

10. The method in accordance with claim 1, the method further comprising:

recording a performance in supplementing the data model with the additional data source.

11. The method in accordance with claim 10, the recording of the performance causing a future response to a request for information from the data model to include the supplemented data contained in the additional data source.

12. The method in accordance with claim 1, the information within the supplemented data model including one or more author defined references to data and one or more supplemented references to data not defined by an author.

13. The method in accordance with claim 1, supplementing occurring prior to formulating the request, supplementing the data model comprising:

modifying the request, such that the modified request is interpreted to cause the supplementing of the data model to occur.

14. The method in accordance with claim 1, wherein the determined supplementation time period comprises either permanently supplementing the data model with the additional data source or supplementing the data model with the additional data source only for purposes of responding to the request.

15. The method in accordance with claim 1, wherein the data model is supplemented with one or more data sources in advance of a request corresponding to the one or more data sources based on an evaluation of potential inputs to one or more functions that are anticipated to be used in the future.

16. A computer program product comprising one or more hardware storage devices having stored thereon computer-executable instructions that are executable by one or more hardware processors of a computing system, to cause the computing system to supplement a data model that includes a plurality of data objects that are each associated with one of a plurality of data types, and a plurality of relationship types that define relationships between data types, the computer-executable instructions including instructions that are executable to cause the computer system to perform at least the following:

receive a request for data from the data model that includes a first data object and a second data object;

in response to receiving the request,

determine that the first data object corresponds to a first data type; and

determine that the second data object does not correspond to any data type known by the data model; and

in response to determining that second data object does not correspond to any data type known by the data model,

correlate the second data object to a second data type;

determine a relationship type between the first data type and the second data type;

based on the second data type or the determined relationship type, identify an additional data source that includes data associated with the second data type;

generate a supplemented data model that comprises the data model and the additional data source;

determine a supplementation time period comprising a time period during which the additional data source supplements the data model; and

respond to the request within the supplementation time period using the supplemented data model.

17. The hardware storage device in accordance with claim 16, wherein determining that the data model does not include the information required to respond to the request is performed in response to determining that a meaning of a controlling value of the request is not referenced in the data model, wherein identifying an additional data source comprises identifying a data source that defines a data type of the controlling value that is not referenced in the data model.

18. The computer hardware storage device in accordance with claim 16, wherein generating the supplemented data model further comprises:

finding relationship data between the data type of the controlling value and the data model; and

incorporating the relationship data into the data model.

19. The computer hardware storage device in accordance with claim 16, wherein identifying the additional data source comprises applying at least one filter to determine that the additional data source includes the information.

20. A computing system, comprising:

one or more processors; and

one or more computer-readable hardware storage devices having stored thereon computer-executable instructions that are executable by the one or more processors to cause the computing system to supplement a data model that includes a plurality of data objects that are each associated with one of a plurality of data types, and a plurality of relationship types that define relationships between data types, the computer-executable instructions including instructions that are executable to cause the computing system to perform at least the following;

receive a request for data from the data model that includes a first data object and a second data object;

in response to receiving the request,

determining that the first data object corresponds to a first data type; and

determining that the second data object does not correspond to any data type known by the data model; and

in response to determining that the second data object does not correspond to any data type known by the data model,

correlating the second data object to a second data type;

determining a relationship type between the first data type and the second data type;

based on the second data type or the determined relationship type, identify an additional data source that includes data associated with the second data type;

generate a supplemented data model that comprises the data model and the additional data source;

determining a supplementation time period comprising a time period during which the additional data source supplements the data model; and

respond to the request within the supplementation time period using the supplemented data model.