@inproceedings{handler-oconnor-2019-query,
title = "Query-focused Sentence Compression in Linear Time",
author = "Handler, Abram and
O{'}Connor, Brendan",
editor = "Inui, Kentaro and
Jiang, Jing and
Ng, Vincent and
Wan, Xiaojun",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-1612",
doi = "10.18653/v1/D19-1612",
pages = "5969--5975",
abstract = "Search applications often display shortened sentences which must contain certain query terms and must fit within the space constraints of a user interface. This work introduces a new transition-based sentence compression technique developed for such settings. Our query-focused method constructs length and lexically constrained compressions in linear time, by growing a subgraph in the dependency parse of a sentence. This theoretically efficient approach achieves an 11x empirical speedup over baseline ILP methods, while better reconstructing gold constrained shortenings. Such speedups help query-focused applications, because users are measurably hindered by interface lags. Additionally, our technique does not require an ILP solver or a GPU.",
}
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%0 Conference Proceedings
%T Query-focused Sentence Compression in Linear Time
%A Handler, Abram
%A O’Connor, Brendan
%Y Inui, Kentaro
%Y Jiang, Jing
%Y Ng, Vincent
%Y Wan, Xiaojun
%S Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F handler-oconnor-2019-query
%X Search applications often display shortened sentences which must contain certain query terms and must fit within the space constraints of a user interface. This work introduces a new transition-based sentence compression technique developed for such settings. Our query-focused method constructs length and lexically constrained compressions in linear time, by growing a subgraph in the dependency parse of a sentence. This theoretically efficient approach achieves an 11x empirical speedup over baseline ILP methods, while better reconstructing gold constrained shortenings. Such speedups help query-focused applications, because users are measurably hindered by interface lags. Additionally, our technique does not require an ILP solver or a GPU.
%R 10.18653/v1/D19-1612
%U https://aclanthology.org/D19-1612
%U https://doi.org/10.18653/v1/D19-1612
%P 5969-5975
Markdown (Informal)
[Query-focused Sentence Compression in Linear Time](https://aclanthology.org/D19-1612) (Handler & O’Connor, EMNLP-IJCNLP 2019)
ACL
- Abram Handler and Brendan O’Connor. 2019. Query-focused Sentence Compression in Linear Time. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 5969–5975, Hong Kong, China. Association for Computational Linguistics.