RICH INDEX TO CLOUD-BASED RESOURCES

• US 20080082490A1
• Filed: 09/28/2006
• Published: 04/03/2008
• Est. Priority Date: 09/28/2006
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: MacLaurin, Matthew B., Meijer, Henricus Johannes Maria, Ozzie, Raymond E., Raghavan, Kartik N., Glasser, Daniel S., Bergstraesser, Thomas F., Connolly, Michael
• Application Number:
  US11/536,440
• Publication Number:
  US 20080082490A1
• Time in Patent Office: Days
• US Class Current: 707/3
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

The innovation enables generation of an index of cloud-based resources (e.g., data, services, applications). The index can be used to retrieve a subset of the cloud-based resources by analyzing a user-generated or standing query. ‘Identity’ and contextual factors can be incorporated to enable rich indexing as well as subsequent retrieval of meaningful resources. The cloud-based resources can be indexed and/or searched in accordance with diverse criteria including, but not limited to, type, size, data created, date modified, author core identity, object size, etc. As well, the innovation can provide for dynamically indexing and/or searching resources in accordance with current contextual factors including, but not limited to, author current acting capacity (e.g., current identity), current engaged activity of a user, location, time, date, etc. All of these criteria can facilitate indexing and categorizing of the resources for later retrieval and rendering via a rich index view.

Claims

1. A system that facilitates indexing a plurality of off-premise resources, comprising:

an index generation component that associates metadata with each of the plurality of off-premise resources, the metadata describes context of a user; and

an index that maintains the metadata associated to each of the resources.

2. The system of claim 1, the plurality of resources are at least one of data, software and a service.

3. The system of claim 1, further comprising an update component that automatically updates the index as a function of a change related to a resource or a change in context;

the update component employs one of a pull, push and publish subscribe mechanism to identify the change.

4. The system of claim 1, further comprising a metadata generation component that automatically generates the metadata as a function of identity of the user.

5. The system of claim 1, further comprising an analysis component that comprises a context analyzer that establishes the context.

6. The system of claim 5, the context includes at least one of a role, an identity, a location, a time, and an activity.

7. The system of claim 1, further comprising an analysis component that comprises an identity determination component that establishes the context of the user.

8. The system of claim 2, further comprising a search component that employs the index to gather a subset of resources associated with the context of the user.

9. The system of claim 8, further comprising a results retrieval component that gathers the subset of resources as a function of the metadata.

10. The system of claim 9, further comprising a results configuration component that configures the subset of resources.

11. The system of claim 10, further comprising a filter component the limits exposure of the subset of resources to the user as a function of the context.

12. The system of claim 10, further comprising a ranking component that categorizes the subset of resources based at least in part upon one of context, a preference and relevance.

13. The system of claim 10, further comprising an ordering component that organizes the subset of resources based at least in part upon one of a preference and relevance.

14. The system of claim 10, further comprising a machine learning and reasoning (MLR) component that employs at least one of a probabilistic and a statistical-based analysis that infers a configuration preferred by the user.

15. The system of claim 1, further comprising a machine learning and reasoning (MLR) component that employs at least one of a probabilistic and a statistical-based analysis that infers a configuration of the index as a function of the metadata.

16. A computer-implemented method of managing a plurality of off-premise resources that correspond to a user, comprising:

analyzing an off-premise resource;

generating metadata associated with the off-premise resource; and

establishing an off-premise index based at least in part upon the metadata.

17. The method of claim 16, further comprising:

locating a change by deducing associations between a subset of the plurality of off-premise resources, deduction includes one of following internal hyperlinks, analyzing external annotations, analyzing tags, or employing artificial intelligence; and

updating the index based at least in part upon the change.

18. The method of claim 16, further comprising establishing context related to the user and incorporating the context into establishing the off-premise index.

19. The method of claim 16, further comprising:

searching the index based upon one of a plurality of identities of the user; and

rendering a subset of the off-premise resources as a function of the identity.

20. A computer-executable system that facilitates management of off-premise resources of a user, comprising:

means for establishing an index associated to a plurality of off-premise resources;

means for updating the index based at least in part upon a change related to a subset of the off-premise resources; and

means for searching the index and identifying a subset of the off-premise resources as a function of an identity of the user.