One of the most convenient ways to query XML data is a keyword search because it does not require any knowledge about XML structure and without the need to learn a new user interface. However, keyword search interface is very flexible. It is hard for a system to decide which node is likely to be chosen as a return node and how much information should be included in the result. To address this challenge, we propose an extension of LCA based XML keyword search. First, to determine a return node, we provide a query syntax that the users can tell the system which node they are really interested in. In case that the users do not explicitly specify return information, our system will automatically analyze and choose appropriate return nodes by inferring from user keywords. Second, to return a meaningful result, we investigate the problem of the return information in the LCA and the proximity search approaches. To this end, we introduce the Lowest Element Node (LEN) and define our simple rules without any requirement on the schema information such as DTD or XML Schema. Our experiment results indicate that our system not only infers the right return nodes but also generates compact and meaningful results.