Keyword search has a friendly user experience; the method has been widely used in the field of text information retrieval. Keyword search on XML data is a hot research topic presently. The XML keyword search method based on query semantics have two problems:(1) a large number of query fragments which are not related to the user's query intention have been returned; (2) the fragments which are consistent with the user's query intention have been missed. Aiming at these problems, two rules of user query intention and LCA correlation are proposed on the basis of the two (horizontal and vertical) dimensions of LCA. The edge density and path density of LCA are defined according to the two rules, and a comprehensive scoring formula on LCA nodes is established, finally, the TopLCA-K algorithm is designed to rank LCA. To improve the efficiency of the algorithm, center location index is designed. Experimental results show that the nodes returned by this method are more in line with the needs of users.