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

摘要

Distributed word representations capture relational similarities by means of vector arithmetics, giving high accuracies on analogy detection. We empirically investigate 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 dependency structures can be used to improve analogy detection by filtering candidates. In addition, we show that distributed representations of dependency structure can be used for measuring relational similarities, thereby help analogy mining.