Search engines have become the main way for people to get expected information, most of them are based on keyword search. However, keyword search is based on computing the similarity of letters of the keywords, instead of semantic meaning, therefore the searching results often include irrelevant information to user intention. This paper aims to find a way on improving keyword search efficiency. Using Wikipedia, which is the largest online encyclopedia, this paper explores the relations of terms through computing the semantic relatedness between words, and presents an algorithm called WLA in the light of link structure and text message in Wikipedia. What is more, we design a terms query platform through which users will be able to get all the meanings about the concepts. By making a comparison with lexical database WordNet, it has demonstrated the feasibility on our methods.