System and method for supporting natural language queries and requests against a user's personal data cloud

1. A database system, comprising:

a memory device having instructions stored thereon that, in response to execution by a processing device, cause the processing device to perform operations comprising:

extracting information from unstructured personal textual data and structured data of a plurality of heterogeneous network sources of data of a personal data cloud of a user, wherein said extraction includes processing at least a portion of the unstructured personal textual data based on an analysis of at least a portion of the structured data;

constructing, using automated semantic analysis that includes one or both of automatic clustering and tagging operations, a semantically indexed, integrated knowledge store for storage and future retrieval of the extracted information, the semantically indexed, integrated knowledge store including information derived algorithmically from the unstructured personal textual data and the structured data;

identifying a natural language user request from the user;

determining a semantic interpretation of the natural language user request, wherein determining the semantic interpretation includes referencing a stored ontology that defines a semantic relationship among a set of personal data terminology;

querying the semantically-indexed, integrated knowledge store based at least in part on the semantic interpretation; and

responding to the natural language user request by displaying one or more results of the querying, wherein the one or more results correspond to at least one item within the personal data cloud.

2. The database system of claim 1 , wherein the operations further include:

soliciting one or more clarifying inputs from the user to disambiguate the natural language user request; and

determining the semantic interpretation based on a result of the solicitation.

3. The database system of claim 1 , wherein the operations further include refining the stored ontology over time based at least in part on machine learning.

4. The database system of claim 1 , wherein the operations further include refining the stored ontology over time based at least in part on interactive user feedback.

5. The database system of claim 4 , wherein the interactive user feedback comprises at least one from a group consisting of:

a star rating mechanism, a thumbs-up or thumbs-down mechanism, and a numbered scale mechanism.

6. An apparatus, comprising:

a processor configured to:

extract information from unstructured personal textual data and structured data of a plurality of heterogeneous network sources of data of a personal data cloud of a user, wherein said extraction includes processing at least a portion of the unstructured personal textual data based on an analysis of at least a portion of the structured data;

construct, using automated semantic analysis that includes one or both of automatic clustering and tagging operations, a semantically indexed, integrated knowledge store for storage and future retrieval of the extracted information, the semantically indexed, integrated knowledge store including information derived algorithmically from the unstructured personal textual data and the structured data;

identify a natural language user request from the user;

determine a semantic interpretation of the natural language user request, wherein the determination of the semantic interpretation includes referencing a stored ontology that defines a semantic relationship among a set of personal data terminology;

query the semantically-indexed, integrated knowledge store based at least in part on the semantic interpretation; and

respond to the natural language user request by displaying one or more results of the query of the semantically-indexed, integrated knowledge store, wherein the one or more results correspond to at least one item within the personal data cloud.

7. The apparatus of claim 6 , wherein the processor is further configured to:

solicit one or more clarifying inputs from the user to disambiguate the natural language user request; and

determine the semantic interpretation based on a result of the solicitation.

8. The apparatus of claim 6 , wherein the processor is further configured to refine the stored ontology over time based at least in part on machine learning.

9. The apparatus of claim 6 , wherein the processor is further configured to refine the stored ontology over time based at least in part on interactive user feedback.

10. The apparatus of claim 9 , wherein the interactive user feedback comprises at least one from a group consisting of:

a star rating mechanism, a thumbs-up or thumbs-down mechanism, and a numbered scale mechanism.

11. The apparatus of claim 6 , wherein the personal textual data comprises user data from at least one of a group consisting of: contacts, calendar events, email, personal notes, to-do lists, shared documents, music, photos, videos, personal financial data, and corporate data.

12. The apparatus of claim 6 , wherein the plurality of heterogeneous network sources of data of the personal data cloud of the user comprise a plurality of network-based user accounts each associated with at least one of a group consisting of: email, social networks, file sharing, calendar(s), media libraries, note-taking applications, enterprise software, CRM, customer support software, corporate wikis, project management software, source code development, and maintenance systems.

13. The apparatus of claim 6 , wherein the natural language user request includes a natural language query, a natural language command, or both.

14. The apparatus of claim 6 , wherein the natural language request comprises one or more automatically suggested words.

15. The apparatus of claim 6 , wherein the processor is further configured to receive and respond to a non-natural language user request received from the user.