A Phrase-Based HMM Approach to Document/Abstract Alignment
Hal Daumé, Daniel Marcu · 2004
We describe a model for creating word-to-word and phrase-to-phrase alignments between documents and their human written abstracts. Such alignments are critical for the development of statistical summarization systems that can be trained on large corpora of document/abstract pairs. Our model, which is based on a novel Phrase-Based HMM, outperforms both the Cut & Paste alignment model (Jing, 2002) and models developed in the context of machine translation (Brown et al., 1993). 1