NEFCIS: Neuro-fuzzy Concept Based Inference System for Specification Mining

In a component based engineering approach, a system can be envisioned as an assembly of reusable and independently developed components. In order to produce automated tools to support the selection and assembly of components, precise selection and retrieval strategies based on product specifications are needed. Conventional approaches use keyword based models for automatically retrieving specification documents that match a set of requirements. These approaches typically fail to mine relationships and spotlight excessively on injective matching. In this paper, we propose a Neuro-fuzzy Concept based Inference System (NEFCIS) which is a novel hybrid expert system approach targeted to extract concepts and retrieve relevant information using the excerpted concepts rather than only keywords. By infusing fuzzy logic into our model, we can process the queries with greater precision and produce deeper knowledge inferences. We describe the basic principles of the proposed methodology and illustrate it with example scenarios.