Abstract
Wikipedia is recognized as one of the largest repositories in the Web. The term knowledge base was in connection with the expert systems as it is the part of Artificial Intelligence. A knowledge base can be created for any entity. The existing system like YAGO, MediaWiki tries to convert Wikipedia into a structured database to provide a vast knowledge base across the domains. It is very difficult to get the information which we want across the domains. So, the solution would be to get a systematic automated approach to build a knowledge base using Wikipedia on entity which we are interested in. The proposed system provides a knowledge base built upon the location as its entity. The system is feeded with seed data, by using these seed data it traverse through the Wikipedia graph and builds knowledge base using similarity measurement between seed data and traversed upcoming pages of wiki graph. Any expert AI systems uses gold standard knowledge base to take any decisions.
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Ganesh, P.E., Manjunath, H.R., Deepashree, V., Kavana, M.G., Raviraja (2020). The New Approach for Creating the Knowledge Base Using WikiPedia. In: Smys, S., Senjyu, T., Lafata, P. (eds) Second International Conference on Computer Networks and Communication Technologies. ICCNCT 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 44. Springer, Cham. https://doi.org/10.1007/978-3-030-37051-0_19
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DOI: https://doi.org/10.1007/978-3-030-37051-0_19
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