Multi-Dimensional Query Expansion Employing Semantics and Usage Statistics

• US 20140337309A1
• Filed: 06/05/2014
• Published: 11/13/2014
• Est. Priority Date: 03/23/2012
• Status: Active Grant

• Current Assignee: SAP SE
• Original Assignee: SAP AG (SAP SE)
• Inventors: Thollot, Raphael, Kuchmann-Beauger, Nicolas, FollenFant, Corentin
• Granted Patent: US 9,690,848 B2
• Time in Patent Office: Days
• US Class Current: 707/709
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: G06F 16/3338 Query expansion
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 2216/03 Data mining

Abstract

Embodiments relate to systems and methods employing personalized query expansion to suggest measures and dimensions allowing iterative building of consistent queries over a data warehouse. Embodiments may leverage one or more of: semantics defined in multi-dimensional domain models, user profiles defining preferences, and collaborative usage statistics derived from existing repositories of Business Intelligence (BI) documents (e.g. dashboards, reports). Embodiments may utilize a collaborative co-occurrence value derived from profiles of users or social network information of a user.

Claims

1. A computer-implemented method comprising:

providing a query expansion system comprising an engine and a data warehouse;

causing the query expansion system to receive a query posed by a user to the data warehouse;

causing the engine to determine a co-occurrence value for the query in the data warehouse based upon social/trust network information taking into account a relationship of the user to another entity in a social/trust network, wherein determining the co-occurrence value comprises applying a weight based upon a distance of the another entity from the user in the social/trust network information; and

causing the query expansion system to display to the user a query result based upon the co-occurrence value.

2. The method of claim 1 wherein the social/trust network information comprises information from a social network.

3. The method of claim 1 wherein the social/trust network information comprises information from an enterprise directory.

4. The method of claim 1 wherein the social/trust network information comprises a business contact.

5. The method of claim 1 wherein the co-occurrence value is further determined from a repository of documents and a user preference.

6. The method of claim 1 wherein the relationship of the user to the other entity in the social/trust network is determined from a user profile.

7. The method of claim 1 wherein determining the co-occurrence value comprises defining a Jaccard index.

8. A non-transitory computer readable storage medium embodying a computer program for performing a method, said method comprising:

providing a query expansion system comprising an engine and a data warehouse;

causing the query expansion system to receive a query posed by a user to the data warehouse;

causing the engine to determine a co-occurrence value for the query in the data warehouse based upon social/trust network information taking into account a relationship of the user to another entity in a social/trust network, wherein determining the co-occurrence value comprises applying a weight based upon a distance of the another entity from the user in the social/trust network information; and

causing the query expansion system to display to the user a query result based upon the co-occurrence value.

9. The non-transitory computer readable storage medium of claim 8 wherein the social/trust network information comprises information from a social network.

10. The non-transitory computer readable storage medium of claim 8 wherein the social/trust network information comprises information from an enterprise directory.

11. The non-transitory computer readable storage medium of claim 8 wherein the social/trust network information comprises a business contact.

12. The non-transitory computer readable storage medium of claim 8 wherein the co-occurrence value is further determined from a repository of documents and a user preference.

13. The non-transitory computer readable storage medium of claim 8 wherein the relationship of the user to the other entity in the social/trust network is determined from a user profile.

14. The non-transitory computer readable storage medium of claim 8 wherein determining the co-occurrence value comprises defining a Jaccard index.

15. A computer system comprising:

one or more processors;

a software program, executable on said computer system, the software program configured to;

provide a query expansion system comprising an engine and a data warehouse;

cause the query expansion system to receive a query posed by a user to the data warehouse;

cause the engine to determine a co-occurrence value for the query in the data warehouse based upon social/trust network information taking into account a relationship of the user to another entity in a social/trust network, wherein determining the co-occurrence value comprises applying a weight based upon a distance of the another entity from the user in the social/trust network information; and

cause the query expansion system to display to the user a query result based upon the co-occurrence value.

16. The computer system of claim 15 wherein the social/trust network information comprises information from a social network.

17. The computer system of claim 15 wherein the social/trust network information comprises information from an enterprise directory.

18. The computer system of claim 15 wherein the social/trust network information comprises a business contact.

19. The computer system of claim 15 wherein the co-occurrence value is further determined from a repository of documents and a user preference.

20. The computer system of claim 15 wherein the relationship of the user to the other entity in the social/trust network is determined from a user profile.