The Development of Intelligent Retrieval Algorithm Ontology-based And Its Application in Bearing production Information System

With the internet technology developing and web information exploding, users urgently need a stronger web information retrieval function. For the better and stronger function, the sequence of search result queue and the correlation of query expression are the key problems that could be computed by similarity algorithm. Now we recommend a new method which is ontology-based weighted semantic tree similarity algorithm (OWSTS). In this paper, we introduce the construction method of OWSTS and the implementation of similarity algorithm. Then we use a deep groove ball bearing as an example to show how to implement intelligent retrieval system for machinery production. Finally the relative accuracy of retrieval results by OWSTS and generally used cosine vector space based similarity algorithm (TF*IDF) are compared. Experiment result shows that OWSTS algorithm is feasible for information retrieval and the similarity algorithm makes the sequence of search result queue fit for users semantic requirement.