Generating complex event processing rules

• US 9,218,163 B2
• Filed: 06/28/2011
• Issued: 12/22/2015
• Est. Priority Date: 06/28/2011
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Dehors, Sylvain, Etzion, Opher, Linehan, Mark H., Rabinovich, Ella
• Primary Examiner(s): VO, HUYEN X
• Application Number:
  US13/170,446
• Publication Number:
  US 20130006608A1
• Time in Patent Office: 1,638 Days
• Field of Search: 704 1- 10, 704/250, 704/251, 704/255, 704/257, 704/270, 707/780
• US Class Current: 1/1
• CPC Class Codes: G06F 8/30 Creation or generation of source code
• CPC Class Codes: G06F 8/41 Compilation

Abstract

Techniques for generating complex event processing rules in a controlled natural language are provided. The techniques include obtaining one or more vocabularies that encompass a set of one or more noun and verb concepts, dynamically building an inheritance hierarchy of one or more named vocabulary concepts from the one or more vocabularies, parsing a controlled natural language input textual statement by using one or more names and the inheritance hierarchy to identify one or more temporal concepts and one or more complex event processing concepts, and converting the controlled natural language input textual statement to a complex event processing language statement by generating a representation of a lexical structure of the controlled natural language input textual statement that contains a reference to each identified temporal and complex event processing concept.

Claims

1. A method for generating complex event processing rules in a controlled natural language, wherein the method comprises steps of:

obtaining one or more controlled natural language vocabularies that encompass a set of one or more noun and verb concepts, wherein the one or more noun concepts comprise one or more sub-types, wherein each sub-type of a noun concept is identified as an example noun categorized under the noun concept;

dynamically building an inheritance hierarchy of one or more named vocabulary concepts from the one or more controlled natural language vocabularies;

parsing a controlled natural language input textual statement, wherein said parsing comprises matching one or more roles in the one or more verb concepts against the controlled natural language input textual statement and using one or more names and the inheritance hierarchy to identify one or more temporal concepts and one or more complex event processing concepts, and wherein said parsing is carried out via a parser component, executing on a hardware processor, that comprises (i) a specified built-in vocabulary and (ii) specified instructions to distinguish defined terms from undefined terms in the controlled natural language input textual statement using the built-in vocabulary;

converting the controlled natural language input textual statement to a complex event processing language statement by generating a representation of a lexical structure of the controlled natural language input textual statement that contains a reference to each identified temporal and complex event processing concept, wherein said converting comprises incorporating one or more synonyms for each identified temporal concept and complex event processing concept; and

outputting the complex event processing language statement to an automated complex event processing system for use in event processing;

wherein each of the steps is carried out by the hardware processor.

2. The method of claim 1, wherein converting the controlled natural language input textual statement to a complex event processing language statement comprises converting one or more definitions of one or more derived events, with associated patterns, filters, aggregations, and contexts, to a specific language expected by a rule engine.

3. The method of claim 1, wherein the one or more vocabularies comprise a built-in vocabulary with a parser module.

4. The method of claim 3, wherein the one or more vocabularies comprise one or more additional vocabularies that extend capabilities of the parser module by defining one or more additional terms for noun concepts and verb concepts.

5. The method of claim 4, wherein the one or more additional vocabularies comprise at least one of a business domain-specific vocabulary and a pre-defined complex event processing vocabulary.

6. The method of claim 5, wherein the pre-defined complex event processing vocabulary comprises at least one of:

definitions and names for one or more derived events;

definitions and names for one or more concepts of one or more stateless and stateful patterns that are used to recognize one or more derived events;

definitions and names for one or more concepts of one or more stateless and stateful filter expressions that are used to include or exclude one or more individual events from further processing;

definitions and terms for one or more concepts of one or more aggregation expressions that are applied to one or more events; and

definitions and terms for a grouping of one or more events that meet specified criteria into one or more named contexts.

7. The method of claim 6, further comprising using one or more names to cross-reference one or more concepts from one or more other definitions and rules.

8. The method of claim 4, wherein the one or more additional vocabularies comprise a pre-defined temporal vocabulary.

9. The method of claim 1, wherein obtaining one or more vocabularies further comprises obtaining one or more input rules, wherein the one or more input rules comprise at least one of definition rules, structural rules and behavioral rules.

10. The method of claim 9, wherein the one or more input rules reference one or more of the one or more noun and verb concepts from the one or more obtained vocabularies.

11. The method of claim 1, wherein parsing a controlled natural language input textual statement comprises using the one or more noun concepts to distinguish one or more defined terms from one or more undefined terms in the input textual statement.

12. The method of claim 1, wherein parsing a controlled natural language input textual statement comprises matching one or more roles in the one or more verb concepts against one or more parsed input textual statement tokens by matching one or more types of the input textual statement tokens against one or more declared types of the one or more roles in the one or more verb concepts.

13. The method of claim 1, further comprising producing an abstract syntax tree from the input textual statement and inputting the abstract syntax tree to a transformation module for conversion to a complex event processing language statement.

14. The method of claim 13, further comprising transforming the abstract syntax tree to an intermediate form.

15. The method of claim 13, wherein inputting the abstract syntax tree to a transformation module for conversion to a complex event processing language statement comprises:

recognizing the reference to each identified temporal and complex event processing concept in the abstract syntax tree and converting each reference to a complex event processing concept in a complex event processing system; and

recognizing one or more applications of one or more temporal and complex event processing concepts in the abstract syntax tree and converting each application to one or more complex event processing semantic relationships in the complex event processing system such that the complex event processing system can recognize one or more derived events from one or more basic events according to one or more complex event processing functions.

16. The method of claim 13, further comprising transforming the abstract syntax tree to one or more rules in a production rule engine.

17. A computer program product comprising a tangible computer readable recordable storage device including computer useable program code for generating complex event processing rules in a controlled natural language, the computer program product including:

computer useable program code for obtaining one or more controlled natural language vocabularies that encompass a set of one or more noun and verb concepts, wherein the one or more noun concepts comprise one or more sub-types, wherein each sub-type of a noun concept is identified as an example noun categorized under the noun concept;

computer useable program code for dynamically building an inheritance hierarchy of one or more named vocabulary concepts from the one or more controlled natural language vocabularies;

computer useable program code for parsing a controlled natural language input textual statement, wherein said parsing comprises matching one or more roles in the one or more verb concepts against the controlled natural language input textual statement and using one or more names and the inheritance hierarchy to identify one or more temporal concepts and one or more complex event processing concepts, and wherein said parsing is carried out via a parser component, executing on a hardware processor, that comprises (i) a specified built-in vocabulary and (ii) specified instructions to distinguish defined terms from undefined terms in the controlled natural language input textual statement using the built-in vocabulary;

computer useable program code for converting the controlled natural language input textual statement to a complex event processing language statement by generating a representation of a lexical structure of the controlled natural language input textual statement that contains a reference to each identified temporal and complex event processing concept, wherein said converting comprises incorporating one or more synonyms for each identified temporal concept and complex event processing concept; and

computer useable program code for outputting the complex event processing language statement to an automated complex event processing system for use in event processing.

18. The computer program product of claim 17, wherein the one or more vocabularies comprise a built-in vocabulary with a parser module and one or more additional vocabularies that extend capabilities of the parser module by defining one or more additional terms for noun concepts and verb concepts, wherein the one or more additional vocabularies comprise at least one of a business domain-specific vocabulary, a pre-defined complex event processing vocabulary and a pre-defined temporal vocabulary.

19. The computer program product of claim 17, further comprising computer useable program code for producing an abstract syntax tree from the input textual statement and inputting the abstract syntax tree to a transformation module for conversion to a complex event processing language statement, wherein the computer usable program code for inputting the abstract syntax tree to a transformation module for conversion to a complex event processing language statement comprises:

computer useable program code for recognizing the reference to each identified temporal and complex event processing concept in the abstract syntax tree and converting each reference to a complex event processing concept in a complex event processing system; and

computer useable program code for recognizing one or more applications of one or more temporal and complex event processing concepts in the abstract syntax tree and converting each application to one or more complex event processing semantic relationships in the complex event processing system such that the complex event processing system can recognize one or more derived events from one or more basic events according to one or more complex event processing functions.

20. A system for generating complex event processing rules in a controlled natural language, comprising:

a memory; and

at least one processor coupled to the memory and operative to;

obtain one or more controlled natural language vocabularies that encompass a set of one or more noun and verb concepts, wherein the one or more noun concepts comprise one or more sub-types, wherein each sub-type of a noun concept is identified as an example noun categorized under the noun concept;

dynamically build an inheritance hierarchy of one or more named vocabulary concepts from the one or more controlled natural language vocabularies;

parse a controlled natural language input textual statement, wherein said parsing comprises matching one or more roles in the one or more verb concepts against the controlled natural language input textual statement and using one or more names and the inheritance hierarchy to identify one or more temporal concepts and one or more complex event processing concepts, and wherein said parsing is carried out via a parser component, executing on a hardware processor, that comprises (i) a specified built-in vocabulary and (ii) specified instructions to distinguish defined terms from undefined terms in the controlled natural language input textual statement using the built-in vocabulary;

convert the controlled natural language input textual statement to a complex event processing language statement by generating a representation of a lexical structure of the controlled natural language input textual statement that contains a reference to each identified temporal and complex event processing concept, wherein said converting comprises incorporating one or more synonyms for each identified temporal concept and complex event processing concept; and

output the complex event processing language statement to an automated complex event processing system for use in event processing.

21. The system of claim 20, wherein the one or more vocabularies comprise a built-in vocabulary with a parser module and one or more additional vocabularies that extend capabilities of the parser module by defining one or more additional terms for noun concepts and verb concepts, wherein the one or more additional vocabularies comprise at least one of a business domain-specific vocabulary, a pre-defined complex event processing vocabulary and a pre-defined temporal vocabulary.

22. The system of claim 20, wherein the at least one processor coupled to the memory is further operative to produce an abstract syntax tree from the input textual statement and input the abstract syntax tree to a transformation module for conversion to a complex event processing language statement, wherein inputting the abstract syntax tree to a transformation module for conversion to a complex event processing language statement comprises:

recognizing the reference to each identified temporal and complex event processing concept in the abstract syntax tree and converting each reference to a complex event processing concept in a complex event processing system; and

recognizing one or more applications of one or more temporal and complex event processing concepts in the abstract syntax tree and converting each application to one or more complex event processing semantic relationships in the complex event processing system such that the complex event processing system can recognize one or more derived events from one or more basic events according to one or more complex event processing functions.