Text summarization via hidden Markov models
Text summarization via hidden Markov models
John M. Conroy,D. O’Leary
2001 · DOI: 10.1145/383952.384042
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval · 398 Citations
TLDR
This work presents an approach to generating sentence extract summary of a document, a hidden Markov model that judges the likelihood that each sentence should be contained in the summary.
Abstract
A sentence extract summary of a document is a subset of the document's sentences that contains the main ideas in the document. We present an approach to generating such summaries, a hidden Markov model that judges the likelihood that each sentence should be contained in the summary. We compare the results of this method with summaries generated by humans, showing that we obtain significantly higher agreement than do earlier methods.