SYSTEMS AND METHODS FOR MANIPULATING DATA USING NATURAL LANGUAGE COMMANDS

• US 20130124194A1
• Filed: 11/13/2012
• Published: 05/16/2013
• Est. Priority Date: 11/10/2011
• Status: Abandoned Application

• Current Assignee: Inventime USA Incorporated
• Original Assignee: Inventive, LLC
• Inventors: Nadal, Francois
• Application Number:
  US13/675,922
• Publication Number:
  US 20130124194A1
• Time in Patent Office: Days
• US Class Current: 704/9
• CPC Class Codes: G06F 16/90332 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 40/40 Processing or translation of natural language natural language analysis G06F40/20; semantic analysis G06F40/30

Abstract

Systems and methods for manipulating data using natural language commands in accordance with embodiments of the invention are disclosed. In one embodiment, a natural language enterprise system includes a database configured to store a natural language index, where the natural language index maps keywords to actions to data, a natural language application server configured to communicate with the database, wherein the natural language application server is configured to receive a command statement, parse the received command statement to identify at least one keyword in the command statement, query the database using at least one keyword to identify at least one actions to data using the natural language index, locate at least one piece of enterprise data to which at least one action to data may be performed, and initiate at least one action to data that is applied to at least one of the located pieces of enterprise data.

Claims

1. A natural language enterprise system, comprising:

a database configured to store a natural language index, where the natural language index maps keywords to actions to data;

a natural language application server configured to communicate with the database;

wherein the natural language application server is configured to;

receive a command statement;

parse the received command statement to identify at least one keyword in the command statement;

query the database using at least one keyword to identify at least one actions to data using the natural language index;

locate at least one piece of enterprise data to which at least one action to data may be performed; and

initiate at least one action to data that is applied to at least one of the located pieces of enterprise data.

2. The natural language enterprise system of claim 1, wherein at least one located piece of enterprise data is stored using the database.

3. The natural language enterprise system of claim 1, wherein at least one located piece of enterprise data is stored using an enterprise data source separate from the natural language enterprise system.

4. The natural language enterprise system of claim 3, wherein the natural language application server initiates at least one action to data that is applied to at least one of the located pieces of enterprise data by providing a command to initiate at least one action to data to the enterprise data source.

5. The natural language enterprise system of claim 1, wherein at least one piece of enterprise data is identified in the command statement.

6. The natural language enterprise system of claim 1, wherein the natural language application server is further configured to:

generate a user interface displaying at least one of the determined actions to data; and

receive a selection of an action to data via the user interface, where the selected action to data is selected from the at least one displayed actions to data.

7. The natural language enterprise system of claim 1, wherein the natural language application server is further configured to generate a list of actions to data using the natural language index, where the list of actions to data comprises actions to data that are relevant to at least one keyword.

8. The natural language enterprise system of claim 1, wherein the natural language application server is further configured to:

determine spelling errors in the received command statement; and

correct the spelling errors.

9. The natural language enterprise system of claim 8, wherein the natural language application server is further configured to:

determine if a spelling error is a neologism; and

ignore the spelling error when it is a neologism.

10. The natural language enterprise system of claim 1, wherein the natural language application server is further configured to identify the language used in the command statement.

11. The natural language enterprise system of claim 10, wherein the natural language application server is further configured to identify the at least one keyword using important words in the command statement, where important words are selected from the group consisting of nouns in the command statement and verbs in the command statement.

12. The natural language enterprise system of claim 1, further comprising:

an indexing server configured to communicate with the natural language application server;

wherein the indexing server is configured to;

receive at least one piece of data from at least one enterprise data source; and

generate a natural language index using the at least one piece of data.

13. The natural language enterprise system of claim 12, wherein the indexing server is further configured to:

generate a relationship tree using the at least one piece of data; and

build a vocabulary;

wherein the generated natural language index indexes the generated relationship tree.

14. The natural language enterprise system of claim 13, wherein the indexing server is further configured to build the vocabulary using the at least one piece of data and a vocabulary source selected from the group consisting of a dictionary and a thesaurus.

15. A method for determining natural language commands, comprising:

receiving a command statement using a natural language enterprise system;

parsing the received command statement to identify at least one keyword in the command statement using the natural language enterprise system;

identifying at least one actions to data using a natural language index and the natural language enterprise system, where the natural language index maps keywords to actions to data;

locating at least one piece of enterprise data to which at least one action to data may be performed using the natural language enterprise system; and

initiating at least one action to data that is applied to at least one of the located pieces of enterprise data using the natural language enterprise system.

16. The method of claim 15, wherein at least one located piece of enterprise data is stored using the natural language enterprise system.

17. The method of claim 15, wherein at least one located piece of enterprise data is stored using an enterprise data source separate from the natural language enterprise system.

18. The method of claim 17, further comprising initiating at least one action to data that is applied to at least one of the located pieces of enterprise data by providing a command using the natural language enterprise system to initiate at least one action to data using the enterprise data source.

19. The method of claim 15, wherein at least one piece of enterprise data is identified in the command statement.

20. The method of claim 15, further comprising:

generating a user interface displaying at least one of the determined actions to data using the natural language enterprise system; and

receiving a selection of an action to data via the user interface using the natural language enterprise system, where the selected action to data is selected from the at least one displayed actions to data.

21. The method of claim 15, further comprising generating a list of actions to data using the natural language index and the natural language enterprise system, where the list of actions to data comprises actions to data that are relevant to at least one keyword.

22. The method of claim 15, further comprising:

determining spelling errors in the received command statement using the natural language enterprise system; and

correcting the spelling errors using the natural language enterprise system.

23. The method of claim 22, further comprising:

determining if a spelling error is a neologism using the natural language enterprise system; and

ignoring the spelling error when it is a neologism using the natural language enterprise system.

24. The method of claim 15, further comprising identifying the language used in the command statement using the natural language enterprise system.

25. The method of claim 24, further comprising identifying the at least one keyword using important words in the command statement using the natural language enterprise system, where important words are selected from the group consisting of nouns in the command statement and verbs in the command statement.

26. The method of claim 15, further comprising:

receiving at least one piece of data from at least one enterprise data source using the natural language enterprise system; and

generating a natural language index using the at least one piece of data and the natural language enterprise system.

27. The method of claim 26, further comprising:

generating a relationship tree using the at least one piece of data and the natural language enterprise system, where the generated natural language index indexes the generated relationship tree; and

building a vocabulary using the natural language enterprise system.

28. The method of claim 27, further comprising building the vocabulary using the natural language enterprise system, the at least one piece of data, and a vocabulary source selected from the group consisting of a dictionary and a thesaurus.

29. A natural language enterprise system, comprising:

a database configured to store a natural language index, where the natural language index maps keywords to actions to data;

a natural language application server configured to communicate with the database;

a natural language indexing server configured to communicate with the database; and

a natural language client device configured to communicate with the natural language application server;

wherein the natural language indexing server is configured to;

receive at least one piece of data from at least one enterprise data source;

generate a relationship tree using the at least one piece of data;

build a vocabulary; and

generate a natural language index using the at least one piece of data, where the generated natural language index indexes the generated relationship tree;

wherein the natural language application server is configured to;

receive a command statement from the natural language client device;

parse the received command statement to identify at least one keyword in the command statement;

query the database using at least one keyword to identify at least one actions to data using the natural language index;

transmit at least one of the identified keywords to the natural language client device;

receive at least one action to data from the client device;

locate at least one piece of enterprise data to which at least one of the received actions to data may be performed; and

initiate at least one of the received action to data that is applied to at least one of the located pieces of enterprise data; and

wherein the natural language client device is configured to;

generate a user interface to receive a command statement;

transmit the received command statement to the natural language application server;

receive at least one determined actions to data;

generate a user interface displaying at least one determined action to data;

receive a selection of an action to data via the user interface, where the selected action to data is selected from the at least one displayed actions to data; and

transmit the selected actions to data to the natural language enterprise system.