Abstract:In order to solve the problem that traditional retrieval techniques based on keywords, concepts and attribute values do not consider the semantic relationship between information in different subjects and can not provide satisfactory information retrieval results to users, a multi-functional information adaptive retrieval technique is studied by semantic Web method. A multi-functional information adaptive retrieval model based on semantic Web is designed. The retrieval model includes human-computer interaction layer, knowledge processing layer and knowledge storage layer. An ontology semantic model is established in the knowledge storage layer. In the knowledge processing layer, the semantic related concepts are inferred from the multi-functional information keywords retrieved, and the original query is expanded according to the related concepts, and the semantic similarity is calculated. In the human-computer interaction layer, user feedback is regarded as a measure factor to judge the quality of retrieval results. Similar result sets are obtained according to similar keywords, and all similar results are sorted according to feedback factors. The sorting results are sent to users to realize multi-functional information adaptive retrieval. The results show that the proposed method can guarantee the recall rate and precision at the same time, the sorting error rate is low, the retrieval results are most consistent with the user's query results, and the retrieval results are accurate and satisfying to users. It is obvious that the retrieval performance of the proposed method is strong.