A Novel Ontology-Based Semantic Retrieval Model for Food Safety Domain

Recently, serious food safety events have emerged frequently and food safety issues have caused wide public concern all over the world. To find the needed food safety information for users from the growing information over the Internet, this paper presents an ontology-based semantic retrieval model used in food safety domain information retrieval. Firstly, food safety domain ontology is constructed to represent food safety domain knowledge, which has many advantages, such as sharable, reusable, and scalable. So it is very appropriately to describe the semantic relationships between food safety domain concepts. Then the lexicon for words segmentation is expanded based on the food safety domain ontology to return more accurate preprocessing results of queries. Finally semantic query expansion and sorting algorithm of search results based on concepts similarity computation model are implemented so that more relevant results can come before irrelevant retrieval results. The experiments show that the precision of the retrieval method with the proposed model is higher 25.2% averagely than that of the traditional retrieval method.