A syntax-free approach to Japanese sentence compression
Tsutomu Hirao, Jun Suzuki, Hideki Isozaki · 2009
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 on-demand 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-the-art conventional technique. Because our method does not use a syntactic parser, it is 4.3 times faster than Hori's method.