Name
Abstract | ||
|---|---|---|
Extracting knowledge from a semantic network may be viewed as a process of finding given patterns in the network. On a von Neumann computer architecture the semantic net is a passive data structure stored in memory and manipulated by a program. This paper demonstrates that by adopting a data-driven model of computation the necessary pattern-matching process may be carried out on a highly-parallel dataflow architecture. The model is based on the idea of representing the semantic network as a dataflow graph in which each node is an active element capable of accepting, processing, and emitting data tokens traveling asynchronously along the network arcs. These tokens are used to perform a parallel search for the given patterns. Since no centralized control is required to guide and supervise the token flow, the model is capable of exploiting a computer architecture consisting of large numbers of independent processing elements. |
Year | DOI | Venue |
|---|---|---|
1985 | 10.1016/0004-3702(85)90054-2 | Expert systems |
Keywords | Field | DocType |
dataflow architecture,semantic net | Dataflow architecture,Computer science,Theoretical computer science,Semantic network,Dataflow,Model of computation,Systems architecture,Von Neumann architecture,Semantic computing,Data flow diagram | Journal |
Volume | Issue | ISSN |
27 | 2 | 0004-3702 |
ISBN | Citations | PageRank |
0-8186-8904-8 | 6 | 6.89 |
References | Authors | |
4 | 1 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lubomir Bic | 1 | 332 | 125.18 |