A domain case-based knowledge model for supporting of high-level information retrieval using reducing ambiguity in language

This study is about a domain cased-based knowledge base model that can improve the level of human value judgement and decision for information retrieve as reducing a ambiguity in language. The big data problem occurred which is decreased the user confidence in search result by a dramatic increase of data or information, and The increasing use of mobile device, is emphasized to increase the simplicity that reduce the human involvement for searching and deciding of result. Therefore, in this study, for increasing the information retrieve performance in area of needing the high-level decision. Indeed, this study has the objective as search for improved performance that required high-level decision-making in the field. For showing high-level concepts or knowledge, in a specific domain area, we used TBox and RBox search and inference mechanism for solving the ambiguity in language. In order to improve search performance which represented concepts, on the processing of knowledge base design and quality through the use of qualified, and is to validate the configuration. Drugs that require expertise in the field of knowledge base Search performance analysis of the knowledge base, Keyword-based search with the ambiguity of the language problem can be solved.