基于有效上下文信息的变体词还原方法

In social networks, people often creates morphs to replace some entity names. How to resolve these morphs to their real target entities is a very important task for natural language processing. In order to overcome the shortcomings that existing methods cannot resolve morphs accurately, this paper proposed a morph resolution method based on effective context information. This method extracted the effective context information of morphs and target candidates, and integrated the effective context information into autoencoders in order to get more accurate embedding of morphs and their target candidates. This method then calculate the similarity between morphs and target candidates based on the accurate embeddings, and ranked the target candidates according to the similarity. The experiments show that this approach significant outperforms the state-of-the-art methods and improves the accuracy of morph resolution.