Yang, 2022 - Google Patents
Extraction of UML class diagrams from natural language specificationsYang, 2022
View PDF- Document ID
- 388047913724435565
- Author
- Yang S
- Publication year
External Links
Snippet
In model-driven engineering, UML class diagrams serve as a way to plan and communicate between developers. In this thesis, we propose an automated approach for the extraction of UML class diagrams from natural language software specifications. To develop our …
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/28—Processing or translating of natural language
- G06F17/2872—Rule based translation
- G06F17/2881—Natural language generation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2705—Parsing
- G06F17/271—Syntactic parsing, e.g. based on context-free grammar [CFG], unification grammars
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2785—Semantic analysis
- G06F17/279—Discourse representation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2765—Recognition
- G06F17/277—Lexical analysis, e.g. tokenisation, collocates
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30634—Querying
- G06F17/30657—Query processing
- G06F17/30675—Query execution
- G06F17/30684—Query execution using natural language analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/274—Grammatical analysis; Style critique
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/3071—Clustering or classification including class or cluster creation or modification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/21—Text processing
- G06F17/22—Manipulating or registering by use of codes, e.g. in sequence of text characters
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/21—Text processing
- G06F17/24—Editing, e.g. insert/delete
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F15/00—Digital computers in general; Data processing equipment in general
- G06F15/18—Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computer systems based on specific mathematical models
- G06N7/005—Probabilistic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/10—Requirements analysis; Specification techniques
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Pais et al. | NLP-based platform as a service: a brief review | |
| Lucassen et al. | Extracting conceptual models from user stories with Visual Narrator | |
| Yang et al. | Towards automatically extracting UML class diagrams from natural language specifications | |
| US20100083215A1 (en) | Method and an apparatus for automatic extraction of process goals | |
| Humphreys et al. | Populating legal ontologies using semantic role labeling: L. Humphreys et al. | |
| Diamantopoulos et al. | Software requirements as an application domain for natural language processing | |
| dos Santos et al. | Automatic user story generation: a comprehensive systematic literature review | |
| Litvin et al. | Ontology-driven development of dialogue systems | |
| Friedrich | Automated generation of business process models from natural language input | |
| Jain et al. | Ontology-based natural language processing for sentimental knowledge analysis using deep learning architectures | |
| Sunkle et al. | AI-driven streamlined modeling: experiences and lessons learned from multiple domains | |
| Calle Gallego et al. | QUARE: towards a question-answering model for requirements elicitation | |
| Budin | Ontology-driven translation management | |
| Murtazina et al. | The detection of conflicts in the requirements specification based on an ontological model and a production rule system | |
| Yang | Extraction of UML class diagrams from natural language specifications | |
| Confort et al. | Learning ontology from text: a storytelling exploratory case study | |
| Hou et al. | A model for quantifying the degree of understanding in cross-domain M2M semantic communications | |
| Nazaruka | Processing Use Case Scenarios and Text in a Formal Style as Inputs for TFM-based Transformations. | |
| Valente | Text2Icons: using AI to tell a story with icons | |
| Letsholo | Early-Stage Requirements Transformation Approaches: A Systematic Review | |
| Xue et al. | Constructing Controlled English for Both Human Usage and Machine Processing. | |
| Arbizu | Extracting knowledge from documents to construct concept maps | |
| Okafor et al. | Designing a semantic analysis framework for intelligent learning by reading systems using advanced text comprehension techniques | |
| Jali et al. | Behavioral model generation from use cases based on ontology mapping and GRASP patterns | |
| Litvin et al. | A dialogue system based on ontology automatically built through a natural language text analysis |