Research Of Vertical Retrieval Engine For Food Safety Based On Ontology

Newly, some food safety events started to attract attention when it happened. There is unified food safety information platform in our country, but the function is not ok when people want to get full and accurate and timely information about food safety. Therefore, it is necessary to construct a web site as public information platform which can collect food safety information which scattered in network.With the rapid development of the Search engine technology, vertical search engine of certain field were constructed. Based on ontology the precision of search engine could been promoted, so some of search engine use technology of ontology. In addition, Food safety standards are informative with the formulation of food safety regulations. By these standards, we can construct domain ontology of food safety. And by application of this ontology, we can also promote the ability of detect food safety information. The key problem of topic search is how to promote the performance of focused crawler, which based on ontology.Therefore this paper analyze network characteristics of official web site and forum, and list the distinguish search algorithms between them. This paper proposed a combined strategy that searched food safety topic on the Internet based on analyzing focused crawler’s searching algorithm. The combined strategy included page-searching and relativity analysis which based on ontology. This paper use improved Fish-Search algorithm and ontology in relativity analysis, then use Vector space model algorithm to find out the great topic in the rough. Then respectively adopted Native Bayes algorithm and improved k Nearest Neighbors classification algorithm to select the correlative small topic from the previous step’s result. By testing the data of some kinds of website the combined searching strategy which based on ontology could improves the harvest ratio and small topic search’s efficiency of the focused crawler system.