A Comparative Study of Inference Engines

Understanding and using the data and knowledge encoded in semantic web documents requires an inference engine. Inference engines, also called reasoners, are software applications that derive new facts or associations from existing information. Inference and inference rules allow for deriving new data from data that is already known. Thus, new pieces of knowledge can be added based on previous ones. By creating a model of the information and relationships, we enable reasoners to draw logical conclusions based on the model. The use of inference engines in the semantic web allows applications to inquire why a particular conclusion has been reached, i.e. semantic applications can give proof of their conclusions. Proof traces or explains the steps involved in logical reasoning. This paper is a survey and study work, which presents a comparison of different types of inference engines in context of semantic web. It will enable to differentiate among different types of inference engines which may be beneficial to realize the various proposed prototype systems with different ideas and views on what an inference engine for semantic web should do.