@inproceedings{L16-1493,
 abstract = {In this paper we report a comparison of various techniques for single-document extractive summarization under strict length budgets, which is a common commercial use case (e.g. summarization of news articles by news aggregators). We show that, evaluated using ROUGE, numerous algorithms from the literature fail to beat a simple lead-based baseline for this task. However, a supervised approach with lightweight and efficient features improves over the lead-based baseline. Additional human evaluation demonstrates that the supervised approach also performs competitively with a commercial system that uses more sophisticated features.
},
 address = {Portorož, Slovenia},
 author = {Yashar Mehdad and Amanda Stent and Kapil Thadani and Dragomir Radev and Youssef Billawala and Karolina Buchner},
 booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
 month = {May},
 pages = {3089--3093},
 publisher = {European Language Resources Association (ELRA)},
 title = {Extractive Summarization under Strict Length Constraints},
 url = {https://www.aclweb.org/anthology/L16-1493},
 year = {2016}
}