System and Method for Metadata Enhanced Inventory Management of a Communications System

• US 20160055142A1
• Filed: 08/20/2014
• Published: 02/25/2016
• Est. Priority Date: 08/20/2014
• Status: Active Grant

• Current Assignee: Futurewei Technologies Incorporated (Huawei Investment & Holding Co., Ltd.)
• Original Assignee: Futurewei Technologies Incorporated (Huawei Investment & Holding Co., Ltd.)
• Inventors: Strassner, John Charles
• Granted Patent: US 10,013,414 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 40/205 Parsing
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

A method for management entity operations includes parsing a request to collect data for an entity in a communications system, the parsing to produce a parsed request and dependency information related to the request, and generating sets of model elements in accordance with context tokens and content tokens derived from the parsed request, the content tokens including extrinsic metadata and intrinsic metadata of the parsed request. The method also includes generating a platform-neutral description of results of the request from an optimized graph derived from the sets of model elements, executing the request to collect the data as requested, and storing the data as collected.

Claims

1. A method for management entity operations, the method comprising:

parsing, by a management entity, a request to collect data for an entity in a communications system, the parsing to produce a parsed request and dependency information related to the request;

generating, by the management entity, sets of model elements in accordance with context tokens and content tokens derived from the parsed request, the content tokens including extrinsic metadata and intrinsic metadata of the parsed request;

generating, by the management entity, a platform-neutral description of results of the request from an optimized graph derived from the sets of model elements;

executing, by the management entity, the request to collect the data as requested; and

storing, by the management entity, the data as collected.

2. The method of claim 1, further comprising:

processing the data as collected to produce processed data; and

displaying the processed data.

3. The method of claim 1, wherein parsing the request to collect the data comprises:

performing morphological pre-processing on the request to produce a first request;

performing lexical pre-processing on the first request to produce a second request;

combining the results of the first and second requests to produce a third request;

parsing the third request to produce the parsed request; and

generating part-of-speech tokens from the parsed request.

4. The method of claim 3, wherein parsing the request to collect the data further comprises:

receiving the request; and

validating the request.

5. The method of claim 1, wherein parsing the request to collect the data comprises:

performing lexical pre-processing on the request to produce a fourth request;

parsing the fourth request to produce the parsed request; and

generating part-of-speech tokens from the parsed request.

6. The method of claim 1, wherein generating the sets of model elements comprises:

extracting the context tokens from the parsed request;

mapping the context tokens to a first set of model elements;

extracting the content tokens from the parsed request; and

mapping the content tokens to a second set of model elements.

7. The method of claim 6, wherein generating the platform-neutral description of the results comprises:

combining the first set of model elements and the second set of model elements into a combined set of model elements;

optimizing the combined set of model elements to produce an optimized set of model elements; and

converting the optimized set of model elements into the platform-neutral description of the results.

8. The method of claim 7, wherein generating the platform-neutral description of the results may be augmented by at least one additional annotation.

9. The method of claim 1, wherein generating the sets of model elements comprises:

evaluating content of the request to collect data to produce links between context tokens and the content tokens; and

mapping the links into a model element graph.

10. The method of claim 9, wherein the context tokens comprises request metadata.

11. The method of claim 9, wherein the request comprises user-entered metadata, the method further comprising:

parsing the user-entered metadata to produce context metadata tokens.

12. The method of claim 9, wherein generating the sets of model elements further comprises selecting model elements to use in constructing the model element graph from the links between the context tokens and the content tokens.

13. The method of claim 12, wherein the content tokens comprise content metadata, and wherein the method further comprises:

parsing the content metadata to produce content metadata tokens.

14. The method of claim 13, further comprising:

combining user-entered metadata tokens and the content metadata tokens to produce unified metadata tokens.

15. The method of claim 9, further comprising:

analyzing context metadata tokens and content metadata tokens in accordance with the dependency information;

analyzing the model element graph in accordance with the dependency information; and

modifying the model element graph for each combination of dependency and dependency type in the dependency information.

16. The method of claim 15, further comprising optimizing the modified model element graph after each dependency and dependency type combination.

17. The method of claim 15, further comprising correlating results from analyzing the context metadata tokens and analyzing the model element graph.

18. The method of claim 15, wherein modifying the model element graph comprises:

for each combination of dependency and dependency type in the dependency information,

performing a dependency analysis in accordance with the dependency and dependency type combination to produce a first list of dependencies, and

adjusting the model element graph in accordance with the dependency and dependency type combination.

19. The method of claim 18, wherein performing the dependency analysis comprises:

analyzing relationships between the metadata tokens and the content tokens;

retrieving a template for the dependency and dependency type combination;

populating the template;

determining dependencies in the metadata tokens and the content tokens corresponding to the dependency and dependency type combination;

generating an ordered list of dependencies from the determined dependencies;

generating a second list of dependencies from the model element graph; and

correlating the ordered list of dependencies and the second list of dependencies to produce the first list of dependencies.

20. The method of claim 1, further comprising displaying the data as collected.

21. The method of claim 20, wherein displaying the data as collected comprises:

matching the data as collected with model elements to identify data that corresponds to model elements of an information model;

optimizing the identified data;

annotating the optimized data; and

displaying text present in the identified and annotated data.

22. The method of claim 21, further comprising:

converting the annotated data to an extensible markup language description of the annotated data; and

converting the identified data to the extensible markup language description of the annotated data.

23. A management entity comprising:

a processor configured to parse a request to collect data for an entity in a communications system, the parsing to produce a parsed request and dependency information, to generate sets of model elements in accordance with context tokens and content tokens derived from the parsed request, the content tokens including extrinsic metadata and intrinsic metadata of the parsed request, to generate a platform-neutral description of results of the request from an optimized graph derived from the sets of model elements, and to execute the request to collect the data as requested; and

a memory operatively coupled to the processor, the memory configured to store the data as collected.

24. The management entity of claim 23, wherein the processor is configured to process the data as collected to produce processed data, and to display the processed data.

25. The management entity of claim 23, wherein the processor is configured to perform morphological pre-processing on the request to produce a first request, to perform lexical pre-processing on the first request to produce a second request, combining the results of the first and second requests to product a third request, to parse the third request to produce the parsed request, and to generate part-of-speech tokens from the parsed request.

26. The management entity of claim 23, wherein the processor is configured to perform lexical pre-processing on the request to produce a fourth request, to parse the fourth request to produce the parsed request, and to generate part-of-speech tokens from the parsed request.

27. The management entity of claim 23, wherein the processor is configured to extract the context tokens from the parsed request, to map the context tokens to a first set of model elements, to extract the content tokens from the parsed request, and to map the content tokens to a second set of model elements.

28. The management entity of claim 27, wherein the processor is configured to combine the first set of model elements and the second set of model elements into a combined set of model elements, to optimize the combined set of model elements to produce an optimized set of model elements, and to convert the optimized set of model elements into the platform-neutral description of the results.

29. The management entity of claim 23, wherein the processor is configured to evaluate content of the request to collect data to produce links between context tokens and the content tokens, and to map the links into a model element graph.

30. The management entity of claim 29, wherein the processor is configured to analyze context metadata tokens and content metadata tokens in accordance with the dependency information, to analyze the model element graph in accordance with the dependency information, and to modify the model element graph for each dependency and dependency type in the dependency information.

31. The management entity of claim 30, wherein the processor is configured for each dependency and dependency type combination, to perform a dependency analysis in accordance with the dependency and dependency type combination to produce a first list of dependencies, and to adjust the model element graph in accordance with the dependency and dependency type combination.

32. The management entity of claim 31, wherein the processor is configured to analyze relationships between the metadata tokens and the content tokens, to retrieve a template for the dependency and dependency type combination, to populate the template, to determine dependencies in the metadata tokens and the content tokens corresponding to the dependency and dependency type combination, to generate an ordered list of dependencies from the determined dependencies, to generate a second list of dependencies from the model element graph, and to correlate the ordered list of dependencies and the second list of dependencies to produce the first list of dependencies.

33. The management entity of claim 23, wherein the processor is configured to match the data as collected with model elements to identify data that corresponds to model elements of an information model, to optimize the identified data, to annotate the optimized data, and to display text present in the annotated data.

34. A management environment comprising:

a communications system being managed; and

a management entity operatively coupled to the communications system, the management entity configured to parse a request to collect data for an entity in the communications system, the parsing to produce a parsed request and dependency information, to generate sets of model elements in accordance with context tokens and content tokens derived from the parsed request, the content tokens including extrinsic metadata and intrinsic metadata of the parsed request, to generate a platform-neutral description of results of the request from an optimized graph derived from the sets of model elements, to execute the request to collect the data as requested, and to store the data as collected.

35. The management environment of claim 34, wherein the management entity comprises:

a processor configured to parse the request to collect data for the entity in the communications system, the parsing to produce the parsed request and the dependency information, to generate the sets of model elements in accordance with the context tokens and the content tokens derived from the parsed request, the content tokens including the extrinsic metadata and the intrinsic metadata of the parsed request, to generate the platform-neutral description of results of the request from the optimized graph derived from the sets of model elements, and to execute the request to collect the data as requested; and

a memory operatively coupled to the processor, the memory configured to store the data as collected.