The value methodology that is commonly known as Value Engineering, is a systematic group problem-solving method that has been used for more than fifty years. In a brief review of its application process, consisting of three steps of pre-study, value study and post-study, it is inferred from its structure that various types of knowledge are created during the cycle of its implementation. Due to the different nature of the process of a value study and the resultant production of various types of knowledge with a different structure, we need to use strategies that help us to discover and extract a variety of knowledge. Data mining is one of the strongest knowledge management techniques that contributes to this matter. In other words, it is possible to create a system for discovering, extracting, storing and retrieving a variety of knowledge in value studies by using the concepts of data mining.

This research tries to find methods for discovery, extraction, storage and retrieval of all kinds of repeatable knowledge of value studies that are known as the outcomes of value studies with the data mining approach and using its concepts and one of the most powerful tools of this technique i.e. neural networks.