Linguistic assistant for domain analysis methodology

• US 20030055625A1
• Filed: 05/31/2001
• Published: 03/20/2003
• Est. Priority Date: 05/31/2001
• Status: Abandoned Application

• Current Assignee: Cogentex Incorporated
• Original Assignee: Cogentex Incorporated
• Inventors: Kittredge, Richard, Lavoie, Benoit, Rambow, Owen, Korelsky, Tatiana
• Application Number:
  US09/870,948
• Publication Number:
  US 20030055625A1
• Time in Patent Office: Days
• US Class Current: 704/9
• CPC Class Codes: G06F 40/268 Morphological analysis
• CPC Class Codes: G06F 40/30 Semantic analysis

Abstract

A Linguistic Assistant For Domain Analysis Methodology to help a user define object models from documents such as requirements documents and validate object models against such documents. The approach is domain-independent and language-independent, mainly relying on widely available linguistic resources for the text analysis.

Claims

1. A method of guiding a user in iteratively deriving object models from documents such as requirements documents and validating such object models against documents, comprising the following steps, which may be applied iteratively and interleaved in any order:

a) identifying model elements using parts of speech and frequencies of word base forms and noun phrases in a document;

b) establishing associations between the model elements using collocations and textual contexts of the word base forms and noun phrases corresponding to model elements in the document;

c) validating object models using collocations and frequencies of word baseforms and noun phrases in the document, as well as natural language paraphrases of the models.

2. The method of claim 1, in which step (a) comprises the steps of:

a) identifying classes using noun base forms and noun phrases frequently occurring in the document;

b) identifying attributes using adjective base forms frequently occurring in the document;

c) identifying associations between classes using verb base forms frequently occurring in the document.

3. The method of claim 1, in which the identification in step (a) is established by automatic linguistic processing of the document.

4. The method of claim 1, in which the model elements of step (a) are based on the concepts and notation of the Unified Modeling Language for representing object models.

5. The method of claim 1, in which the model elements of step (a) are based on the concepts and notation of Entity-Relationship models.

6. The method of claim 1, in which step (b) comprises the steps of:

a) declaring associations between classes using collocations and textual contexts of word base forms corresponding to the model elements in the document;

b) associating attributes with classes using collocations and textual contexts of the word base forms corresponding to the model elements in the document;

7. The method of claim 1, in which the collocations and textual contexts are established by automatic linguistic processing.

8. The method of claim 1, in which associations between the model elements of step (b) are based on the concepts and notation of the Unified Modeling Language for representing object models.

9. The method of claim 1, in which the model elements of step (b) and associations between the elements are based on the concepts and notation of Entity-Relationship models.

10. The method of claim 1, in which step (c) comprises the steps of:

a) detecting any missing model elements having corresponding word base forms and noun phrases that occur with high frequency in the document;

b) detecting any model elements with corresponding word base forms and noun phrases that occur with low or zero frequency in the document;

c) detecting any missing associations between classes or between classes and their attributes corresponding to word base forms or noun phrase forms that collocate in the document;

d) verifying the semantics of the model using descriptive paraphrases in natural language.

11. The method of claim 1, in which the natural language paraphrases in step (c) are automatically produced.