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A Knowledge Representation Technique for Intelligent Storage and Efficient Retrieval using Knowledge based Markup Language
Background: Knowledge Engineering is an engineering discipline that involves integrating knowledge into computer systems in order to solve complex problems normally requiring a high level of human expertise. Knowledge Engineering is the technique applied by knowledge engineers to build intelligent systems: Expert Systems, Knowledge Based Systems, Knowledge based Decision Support Systems, Expert Database Systems etc. Methods: This work builds a Knowledge Base using Knowledge Base Markup Language (KBML) which is derived from XML architecture. All the Meta information is stored in a KBML file whereas the actual data may be available in any data source. Findings: This system also provides facilities to search/add the contents to and from the Knowledge Base dynamically. The experimental results show that the system provides a high precision, recall and f-measure values which proves the high relevance of the retrieved values. Applications: Builds an intelligent system for Edaphology domain which concerns with plants and its related soil features. It provides the edaphologists and agriculturists by retrieving relevant and useful information about the plants. This is of huge importance as plant growth and yield are directly dependent on the soil features.
Data Source, Edaphology, Knowledge Base Markup Language, Meta Information
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