With the fast growth of the Web, users often suffer from the problem of information overload since many existing search engines response lots of non-relevant documents containing query terms based on the search mechanism of keyword matching. In fact, it is eagerly expected by both users and search engine developers to reduce overloaded information by understanding user goals clearly. In this paper, we intend to utilize Web search results to identify user goals. We propose one novel probabilistic inference model which effectively employs syntactic features to discover a variety of confined user goals.