A Syntax-Free Approach to Japanese Sentence Compression

Conventional sentence compression methods employ a syntactic parser to compress a sentence without changing its meaning. However, the reference compressions made by humans do not always retain the syntactic structures of the original sentences. Moreover, for the goal of ondemand sentence compression, the time spent in the parsing stage is not negligible. As an alternative to syntactic parsing, we propose a novel term weighting technique based on the positional information within the original sentence and a novel language model that combines statistics from the original sentence and a general corpus. Experiments that involve both human subjective evaluations and automatic evaluations show that our method outperforms Hori’s method, a state-of-theart conventional technique. Because our method does not use a syntactic parser, it is 4.3 times faster than Hori’s method.