Ontology semantic information retrieval model based on user preference

With the development of the Internet, how to quickly and accurately retrieve the information that users need from massive Internet resources is a difficult problem in current information retrieval. The needs of user retrieval are be-coming more and more complex. This makes the keyword-based information retrieval technology gradually showing the problem of information overload, the retrieval result often contains a large amount of information that is in-consistent with the user's preference, resulting in a lower retrieval accuracy. Therefore, this paper proposes an ontology semantic information retrieval model OSIR (Ontology Semantic Information Retrieval) based on users’ preference. The core idea is about three steps: firstly transform the domain ontology into a global ontology, and extract semantics from the global on-tology, and obtain the conceptual logic view through semantic reasoning; then add the user’s preferences in the logical view to make the index words having the characteristics of the user’s preferences; finally Prioritize the semantic relationship between semantic index words with the user’s preferences to improve retrieval accuracy.