International Journal of Intelligent Systems and Applications (IJISA)
IJISA Vol. 8, No. 5, 8 May 2016
Cover page and Table of Contents: PDF (size: 474KB)
Fuzzy-Based XML Knowledge Retrieval Methods in Edaphology
Full Text (PDF, 474KB), PP.55-64
Views: 0 Downloads: 0
Author(s)
Index Terms
Knowledge management, XML, Knowledge Retrieval, Soil, Edaphology, Fuzzy search
Abstract
In this paper, we propose a proficient method for knowledge management in Edaphology to assist the edaphologists and those related with agriculture in a big way. The proposed method mainly consists two sections of which the first one is to build the knowledge base using XML and the latter part deals with information retrieval by searching using fuzzy. Initially, the relational database is converted to the XML database. The paper discusses two algorithms, one is when the soil characteristics are inputted to have the plant list and in the other, plant names are inputted to have the soil characteristics suited for the plant. While retrieving the query result, the crisp numerical values are converted to fuzzy using the triangular fuzzy membership function and matched to those in database. And those which satisfy are added to the result list and subsequently the frequency is found out to rank the result list so as to obtain the final sorted list. Performance metrics used in order to evaluate the method and compare it to baseline paper are number of plants retrieved, ranking efficiency, and computation time and memory usage. Results obtained proved the validity of the method and the method obtained average computation time of 0.102 seconds and average memory usage of 2486 Kb, which all are far better than the previous method results.
Cite This Paper
K. Naresh kumar, Ch. Satyanand Reddy, N.V.E.S. Murthy, "Fuzzy-Based XML Knowledge Retrieval Methods in Edaphology", International Journal of Intelligent Systems and Applications(IJISA), Vol.8, No.5, pp.55-64, 2016. DOI:10.5815/ijisa.2016.05.08
Reference
[1]B. Koester, “Conceptual Knowledge Retrieval with FooCA: Improving Web Search Engine Results with Contexts and Concept Hierarchies”. International Conference on Data Mining, July 2006, pp. 176-190.
[2]B.D. Newman, and K.W. Conrad, “A Framework for Characterizing Knowledge Management Methods, Practices, and Technologies”. In Proceedings of the Third International Conference on Practical Aspects of Knowledge Management, 2000, pp. 30-32.
[3]Y. Li, and Y. Yao, “User profile model: a view from Artificial Intelligence”. In proceedings of 3rd International Conference on Rough Sets and Current Trends in Computing, Oct 14-16 2002, pp. 493-496.
[4]Y. Li, and N. Zhong, “Web Mining Model and its Applications for Information Gathering”. Knowledge-Based Systems, Vol.17, 2004, pp. 207-217.
[5]Y. Li, and N. Zhong, “Mining Ontology for Automatically Acquiring Web User Information Needs, IEEE Transactions on Knowledge and Data Engineering, Vol.18, No.4, 2006, pp. 554-568.
[6]X. Tao, Y. Li, Y, and R. Nayak, “A Knowledge Retrieval Model Using Ontology Mining and User Profiling”. Integrated Computer-Aided Engineering, Vol.15, No.4,
2008, pp. 1-24.
[7]Y. Yao, Yi. Zeng, N. Zhong, and X. Huang, “Knowledge Retrieval (KR)”. In proceedings of IEEE International Conference on Web Intelligence, 2007, pp. 729-735.
[8]M. Apistola, L. Mommers, and A. Lodder, “A Knowledge Management Exercise in the domain of Sentencing: towards an XML Specification”. In: Proceedings of the Second International Workshop on Legal Ontologies, Amsterdam, the Netherlands: December 13, 2001, pp. 49-57.
[9]S. Denning “The role of ICT's in knowledge management for development”. The Courier ACP-EU, Vol.192, 2002, pp. 58 - 61.
[10]R. Irfan, and M. Shaikh, “Enhance Knowledge Management Process for Group Decision Making”. In Proceedings of World Academy of Science, Engineering and Technology, 2009.
[11]J. Whittaker, M. Burns, J.V. Beveren, “Understanding and measuring the effect of social capital on knowledge transfer within clusters of small-medium enterprises”. In proceedings of the 16th Annual Conference of Small Enterprise Association of Australia and New Zealand, 2003.
[12]C. Grinand, D. Arrouays, B. Laroche, and M.P. Martin, “Extrapolating regional soil landscapes from an existing soil map: Sampling intensity, validation procedures, and integration of spatial context”. Geoderma, Vol. 143, Issue 1-2, Jan 2008, pp. 180–190.
[13]E.N. Bui, B.L. Henderson, and K. Viergever, “Knowledge discovery from models of soil properties”. Ecol. Model, Vol.191, 2006, pp. 431–446.
[14]E.N. Bui, “Soil survey as a knowledge system”. Geoderma, Vol.120, May 2004, pp.17–26.
[15]R. Irfan, and M. Uddin-Shaikh, “Enhance Knowledge Management Process for Group Decision Making”. In Proceedings of World Academy of Science, Engineering and Technology, World Congress on Science, Engineering and Technology (WCSET 2009), Penang, Malaysia, February 2009.
[16]A. Meenakshi, and V. Mohan, “An Efficient Tree-Based System for Knowledge Management in Edaphology”. European Journal of Scientific Research, Vol.42, No.2, 2010, pp. 253-267.
[17]L.L Ralph, and T.J. Ellis, “An Investigation of a Knowledge Management Solution for the Improvement of Reference Services”. Journal of Information, Information Technology, and Organizations, Vol. 4, 2009, pp. 17-38.
[18]Q. Yang, J. Yin, Ch. Ling, R. Pan, “Extracting Actionable Knowledge from Decision Trees”. IEEE Transaction on Knowledge and data Engineering, Vol.19, No.1, 2007, pp.43-56.
[19]R. Farenhorst, and R.C. de Boer, “Knowledge Management in Software Architecture: State of the Art”. Software and Architecture Management, 2009, pp. 1-277.