Name
Abstract | ||
|---|---|---|
The parsing of natural language is the product of dense interactions among various comprehension processes. We believe that traditional models have greatly underestimated the richness of these interactions. We propose a model for low-level parsing which is massively parallel, highly distributed, and highly connected. The model suggests a solution to the problem of word sense disambiguation which is psychologically plausible and computationally feasible. The paper outlines the general connectionist paradigm followed by a brief description of a three-level network to do parsing. Finally we trace through an example to illustrate the functioning of the model. |
Year | Venue | Field |
|---|---|---|
1982 | AAAI | Massively parallel,Computer science,Bottom-up parsing,Natural language,Natural language processing,Artificial intelligence,Parsing,Machine learning,Word-sense disambiguation,Connectionism,Comprehension |
DocType | Citations | PageRank |
Conference | 11 | 2.10 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Steven L. Small | 1 | 158 | 22.15 |
| Garrison W. Cottrell | 2 | 1397 | 286.59 |
| Lokendra Shastri | 3 | 300 | 91.85 |