Towards Purpose Driven Content Interaction Modeling and Processing based on DIKW

Abstract

In this information and regularization era, people will encounter a variety of forms in their daily life and office, such as online shopping to fill in the recipient information, travel to fill in the epidemic prevention information and so on. People classify these as content filling problems. In the face of these forms, there are many problems, such as repeated filling, error, troublesome, leakage of information and so on. However, existing automatic filling technology often only stays at the level of data or information migration, which is difficult to deal with the above problems. Moreover, it does not analyze purpose of the preparer and the form in the filling process. This is easy to produce filling behavior contrary to purpose of the preparer. Aiming at this kind of problem, we proposes a content filling data, information, knowledge and purpose(DIKP) modeling method. This method transforms the contents of preparer and form into data, information, knowledge and purpose, and establishes DIKP system. Then, driven by the purpose of the preparer, we fully analyze and calculate the DIKP systems of preparer and form. We judge and grade the filling value. We fill the content through the methods such as comparison of purpose, reducing uncertainty, fuzzy transmission and content verification to achieve intelligence and rationality.