The connection machine
Integrating Marker Passing and Problem Solving: A Spreading Activation Approach to Improved Choice in Planning
A Parallel System for Text Inference Using Marker Propagations
IEEE Transactions on Parallel and Distributed Systems
A new parallel LR parsing algorithm
SAC '95 Proceedings of the 1995 ACM symposium on Applied computing
Parallel Natural Language Processing on a Semantic Network Array Processor
IEEE Transactions on Knowledge and Data Engineering
A Parallel Algorithm for Text Inference
IPPS '96 Proceedings of the 10th International Parallel Processing Symposium
Parallel Inference on a Linguistic Knowledge Base
IPPS '97 Proceedings of the 11th International Symposium on Parallel Processing
TextNet – A text-based intelligent system
Natural Language Engineering
Marker-Passing inference in the scone knowledge-base system
KSEM'06 Proceedings of the First international conference on Knowledge Science, Engineering and Management
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The semantic network array processor (SNAP), a highly parallel architecture targeted to artificial intelligence applications, and in particular natural language understanding, is presented. The knowledge is represented in a form of the semantic network. The knowledge base is distributed among the elements of the SNAP array, and the processing is performed locally where the knowledge is stored. A set of powerful instructions specific to knowledge processing is implemented directly in hardware. SNAP is packaged into 256 custom-designed chips assembled on four printed circuit boards and can store a 16 K node semantic network. SNAP is a marker propagation architecture in which the movement of markers between cells is controlled by propagation rules. Various reasoning mechanisms are implemented with these marker propagation rules.