Study on the Application of Frequent Sub-tree Patterns in Focus Words Recognition

In the field of Chinese Focus-words Recognition, current studies don't take full advantages of some deep statistical relationships in dependency syntax. To solve this problem and explore statistical relationships between Chinese focus words and the multiple properties of words, a new concept called Multi-Dimensional Tree (MDT) and a solution of mining frequent MDT pattern are proposed and applied. Solutions of condensing those frequent patterns and dealing with pattern conflicts are given, a Chinese focus words recognizer is trained. The method is a kind of typical objective method, the empirical results show that this method is good at stability, adaptability and robustness and can reach higher recognition accuracy rate than CRF model.