RESEARCH ON ONTOLOGY-BASED LITERATURE RETRIEVAL MODEL
Zhijun Zhang1, 2, 3, Hong Liu1, 2
1 School of Information Science and Engineering, Shandong Normal University, Jinan 250014, China
2 Shandong Provincial Key Laboratory for Novel Distributed Computer Software, Jinan 250014, China
3 School of Computer Science and Technology, Shandong Jianzhu University, Jinan 250101, China
Proper understanding of textual data requires the exploitation and integration of unstructured and heterogeneous scientific literature, which are fundamental aspects in literature retrieval research. The traditional literature retrieval is based on keyword matching, and the retrieval results often deviating from the users' needs. In this paper from the perspective of ontology, we built shareable and relatively perfect medical enzyme ontology, which is the foundation of the study of domain ontology constructing method. The ontology-based full text retrieval algorithm is put forward, and a document retrieval system based on medical enzyme semantics is designed and implemented, which can not only implement intelligent literature retrieval, but also improve the recall significantly while keeping high precision. This system can employ in particular area moreover it can be used in different areas of the semantic retrieval, which can provide intelligent foundation for the expert systems in medical enzymes field, information retrieval and natural language understanding, etc. The experimental results on the public medical enzyme domain dataset show that our approach performs better than the state-of-the-art methods.