Knowledge Reduction Information Retrieval Model in Pathology Medical Domain

We present an efficient intelligent information retrieval model using reduction of domain-specific expert knowledge, demonstrating its use in the pathology medical domain. We created an information retrieval model that incorporates domain-specific knowledge to provide knowledgeable answers to users. This model converts domain-specific knowledge to a relationship of terms represented as quantitative values, which gives improved efficiency. The conversion technology, called “knowledge reduction,” enables the off-line calculation of knowledge separate from the information retrieval (IR) process. This results in the real-time processing of retrieval results. We performed a simulation of the developed Intelligent IR model in the Pathology medical domain. Our approach resulted in an approximately 30% performance gain measured by average precision at 11 standard recall levels metrics when compared with the vector space model based IR method.