Syntactic Dependencies and Distributed Word Representations for Chinese Analogy Detection and Mining

Distributed word representations capture relational similarities by means of vec-tor arithmetics, giving high accuracies on analogy detection. We empirically inves-tigate the use of syntactic dependencies on improving Chinese analogy detection based on distributed word representation-s, showing that a dependency-based em-beddings does not perform better than an ngram-based embeddings, but dependen-cy structures can be used to improve anal-ogy detection by filtering candidates. In addition, we show that distributed repre-sentations of dependency structure can be used for measuring relational similarities, thereby help analogy mining.