Using semantic and context features for answer summary extraction

Yulianti, E, Chen, R, Scholer, F and Sanderson, M 2016, 'Using semantic and context features for answer summary extraction', in S. Karimi and M. Carman (ed.) Proceedings of the 21st Australasian Document Computing Symposium, Melbourne, Australia, 5-7 December 2016, pp. 81-84.


Document type: Conference Paper
Collection: Conference Papers

Title Using semantic and context features for answer summary extraction
Author(s) Yulianti, E
Chen, R
Scholer, F
Sanderson, M
Year 2016
Conference name ADCS 2016
Conference location Melbourne, Australia
Conference dates 5-7 December 2016
Proceedings title Proceedings of the 21st Australasian Document Computing Symposium
Editor(s) S. Karimi and M. Carman
Publisher Association for Computing Machinery (ACM)
Place of publication United States
Start page 81
End page 84
Total pages 4
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.
Subjects Information Retrieval and Web Search
Keyword(s) summarization
answer summaries
non-factoid queries
DOI - identifier 10.1145/3015022.3015031
Copyright notice © 2016 ACM.
ISBN 9781450348652
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