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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 10, 2020.
Abstract: Extraction method of keywords for retrieval from paper documents and drawings based on the method of determining the importance of knowledge by the Analytic Hierarchy Process: AHP method is proposed. The method allows distinguish the documents into three categories, letter, form and drawing types of documents, then the most appropriate knowledge about keyword for retrievals, font size, location, frequency of the words etc. are selected for each document type. Production rules are created with more than five of the knowledge on keywords for retrievals. Traditional production system employs isolated knowledge so that it is not easy to take overall suitability of the knowledge. In order to overcome this situation, AHP is employed in the proposed system. Through experiments with 100 documents and diagrams, 98% success rate is achieved, and it is found that appropriate candidates for keywords with likelihood or certainty factor can be extracted with the proposed system. The proposed production system shows 50% of improvement on success rate of the keywords extraction from documents and diagrams compared to the existing production system without AHP.
Kohei Arai, “Extraction of Keywords for Retrieval from Paper Documents and Drawings based on the Method of Determining the Importance of Knowledge by the Analytic Hierarchy Process: AHP” International Journal of Advanced Computer Science and Applications(IJACSA), 11(10), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0111007
@article{Arai2020,
title = {Extraction of Keywords for Retrieval from Paper Documents and Drawings based on the Method of Determining the Importance of Knowledge by the Analytic Hierarchy Process: AHP},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0111007},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0111007},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {10},
author = {Kohei Arai}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.