@inproceedings{88cbac64320e4dc2b0e97c793ccf810a,
title = "Using semantic and context features for answer summary extraction",
abstract = "We investigate the effectiveness of using semantic and context features for extracting document summaries that are designed to contain answers for non-factoid queries. The summarization methods are compared against state-of-the-art factoid question answering and query-biased summarization techniques. The accuracy of generated answer summaries are evaluated using ROUGE as well as sentence ranking measures, and the relationship between these measures are further analyzed. The results show that semantic and context features give significant improvement to the state-of-the-art techniques.",
keywords = "Answer summaries, Non-factoid queries, Summarization",
author = "Evi Yulianti and Chen, {Ruey Cheng} and Falk Scholer and Mark Sanderson",
note = "Funding Information: This work was supported by the Australian Research Council (DP140102655) and the Indonesia Endowment Fund for Education (LPDP). Publisher Copyright: {\textcopyright} 2016 ACM.; 21st Australasian Document Computing Symposium, ADCS 2016 ; Conference date: 06-12-2016 Through 07-12-2016",
year = "2016",
month = dec,
day = "5",
doi = "10.1145/3015022.3015031",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "81--84",
editor = "Sarvnaz Karimi and Mark Carman",
booktitle = "ADCS 2016 - Proceedings of the 21st Australasian Document Computing Symposium",
address = "United States",
}