Pattern Generation

• US 20070213973A1
• Filed: 06/10/2006
• Published: 09/13/2007
• Est. Priority Date: 03/08/2006
• Status: Active Grant

• Current Assignee: Trigent Software Ltd.
• Original Assignee: Trigent Software Ltd.
• Inventors: Goel, Amit, Satyanarayana, Krishnamurthy, Comandur, Vasudevan, Seshadri, Rengarajan, Rehberg, Charles, Mehta, Abhishek
• Granted Patent: US 8,423,348 B2
• Time in Patent Office: Days
• US Class Current: 704/9
• CPC Class Codes: G06F 40/295 Named entity recognition

Abstract

A method and system is disclosed herein for generating a plurality of equivalent sentence patterns from a declared sentence pattern for a specific language. The declared pattern is fed into a pattern generator. The pattern generator reads a predetermined library of equivalent pattern specification sets and selects an equivalent pattern specification set for the declared pattern. The equivalent patterns and declared pattern are fed to a rules generator. The rules generator outputs executable semantic pattern recognition rules. The reader module, using the generated executable semantic pattern recognition rules, reads the given information source to determine the information of interest.

Claims

1. A method of generating a plurality of equivalent patterns from a declared pattern for a specific language, given a reading style of a user, comprising the steps of:

providing a declared sentence pattern, wherein said declared sentence pattern is determined from the reading style of a user;

providing equivalent pattern specification sets representing the grammar for said specific language;

determining the matching equivalent pattern set for said declared pattern from said equivalent pattern specification sets;

mapping pattern variables within said matched equivalent set with equivalent name sets of the declared pattern units; and

substituting said pattern variables with equivalent sets to generate equivalent pattern sets.

2. A method of applying equivalent patterns to an information source for determining the information of interest from an information source for an end user, comprising the steps of:

inputting said equivalent patterns;

providing and applying a specification of a target rules language format to said equivalent patterns to generate executable semantic pattern recognition rules;

identifying the section of the information source that requires processing, wherein said step of identifying is directed by the reading plan of said end user;

reducing said identified section of the information source to semantic items;

providing a library of equivalent name sets;

substituting each of said semantic units with corresponding equivalent name sets selected from said library of equivalent name sets, thereby creating equivalent name set enhanced semantic units; and

,

applying said equivalent patterns and said executable semantic pattern recognition rules to said equivalent name set enhanced semantic units to generate the information of interest.

4. The method of claim 2, further comprising the step of resolving references, comprising the steps of:

identifying reference items that are words or phrases that require resolution;

determining if a language specific context contains an equivalent name set substitution for said reference item;

wherein said language specific context is created updated for each identified pattern at run time with the role, number and any other distinguishing factors; and

substituting said equivalent name set substitution for the reference item.

6. The method of claim 2, wherein a semantic unit comprises words, sentences or paragraphs.

3. A method of applying equivalent sentence patterns to an information source for determining the information of interest for an end user, comprising the steps of:

inputting said equivalent sentence patterns;

providing and applying a specification of the target rules language format to said equivalent patterns to generate executable semantic pattern recognition rules;

identifying the section of the information source that requires processing, wherein said step of identifying is directed by the reading plan of said end user;

reducing said identified section of the information source to semantic items;

providing a library of equivalent name sets;

substituting each of said semantic units with corresponding equivalent name sets derived from said library of equivalent name sets, thereby creating equivalent name set enhanced semantic units; and

decomposing compound sentences of said equivalent name set enhanced semantic units to generate simplified equivalent name set enhanced semantic units; and

applying said equivalent patterns and said executable semantic pattern recognition rules to said simplified equivalent name set enhanced semantic units to generate the information of interest.

5. The method of claim 3, wherein the step of providing and applying a specification of the target rules language format to said equivalent patterns, further comprises the step of applying grammar logic using a grammar function signature specification, wherein said grammar function signature specification further comprises:

an instance-level equivalent name set function that is an interface definition to a function that handles the equivalent name sets;

an instance-level number function that is an interface definition to a function that handles singular and plural forms of a word;

an instance-level reference resolution function that is an interface definition to a function that handles the resolution of pronouns; and

an instance-level tense function that is an interface definition to a function that handles the different forms of a verb.