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Constructing VEGGIE: Machine Learning for
| Content Provider | CiteSeerX |
|---|---|
| Author | Grammars, Context-Sensitive Graph |
| Abstract | Context-sensitive graph grammar construction tools have been used to develop and study interesting languages. However, the high dimensionality of graph grammars result in costly effort for their construction and maintenance. Additionally, they are often error prone. These costs limit the research potential for studying the growing graph based data in many fields. As interest in applications for natural languages and data mining has increased, the machine learning of graph grammars poses a prime area of research. A unified graph grammar construction, parsing, and inference tool is proposed. Existing technologies can provide a context-free tool. However, a general context-sensitive tool has been elusive. Using existing technologies for graph grammars, a tool for the construction and parsing of context-sensitive graph grammars is combined with a tool for inducing context-free graph grammars. The system is extended with novel work to infer contextsensitive graph grammars. 1. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Research Potential Prime Area Many Field Contextsensitive Graph Grammar Costly Effort Data Mining Interesting Language General Context-sensitive Tool Unified Graph Grammar Construction Machine Learning Context-free Tool Graph Grammar Inference Tool Novel Work High Dimensionality Context-free Graph Grammar Context-sensitive Graph Grammar Context-sensitive Graph Grammar Construction Tool Error Prone Natural Language |
| Content Type | Text |
