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| Gerard Ellis, "Compiling Conceptual Graphs," IEEE Transactions on Knowledge and Data Engineering, vol. 7, no. 1, pp. 68-81, February, 1995. | |||
| BibTex | x | ||
| @article{ 10.1109/69.368517, author = {Gerard Ellis}, title = {Compiling Conceptual Graphs}, journal ={IEEE Transactions on Knowledge and Data Engineering}, volume = {7}, number = {1}, issn = {1041-4347}, year = {1995}, pages = {68-81}, doi = {http://doi.ieeecomputersociety.org/10.1109/69.368517}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Knowledge and Data Engineering TI - Compiling Conceptual Graphs IS - 1 SN - 1041-4347 SP68 EP81 EPD - 68-81 A1 - Gerard Ellis, PY - 1995 KW - Associative retrieval KW - compilation KW - conceptual graphs KW - hierarchical knowledge bases KW - partial orders. VL - 7 JA - IEEE Transactions on Knowledge and Data Engineering ER - | |||
We give an improved algorithm for classifying conceptual graphs into this hierarchy. It prunes the search space in the database using the information gathered while searching.
We show how conceptual graphs in this hierarchy can be compiled into instructions which represent specialized cases of the canonical formation rules. This compiles subsumption of conceptual graphs and compresses knowledge in a knowledge base. Conceptual graphs are compiled as differences between adjacent graphs in the hierarchy. The differences represent the rules used in deriving the graph from the adjacent graphs. We illustrate how the method compresses knowledge bases in some experiments.
Compilation is effected in three ways: removal of redundant data, use of simple instructions which ignore redundant checks when performing matching, and by sharing common processing between graphs.
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