Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)

Research on Summary Sentences Extraction Oriented to Chinese Patent

Authors
Lei Wang, Xueqiang Lv, Xindong You
Corresponding Author
Xindong You
Available Online April 2019.
DOI
https://doi.org/10.2991/icmeit-19.2019.61How to use a DOI?
Keywords
Chinese patent summarization; learning to rank; semantic weigh; word2vec.
Abstract
In this paper, it describes our system oriented to single document summarization task at Chinese patent. We treat the task as a typical document summarization based on sentence extraction and decide to formulate the task in a supervised learning to rank framework, utilizing both common sentence features including term frequency, sentence position, sentence length for generic document summarization and specially designed semantic weigh feature. Summary sentence are selected according the scores by the LTR model we trained from the patent specification. Evaluation results show that our method is indeed appropriate for this task, outperforming several baseline methods in different aspects.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Computer Science Research
Publication Date
April 2019
ISBN
978-94-6252-708-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmeit-19.2019.61How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Lei Wang
AU  - Xueqiang Lv
AU  - Xindong You
PY  - 2019/04
DA  - 2019/04
TI  - Research on Summary Sentences Extraction Oriented to Chinese Patent
PB  - Atlantis Press
SP  - 372
EP  - 376
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-19.2019.61
DO  - https://doi.org/10.2991/icmeit-19.2019.61
ID  - Wang2019/04
ER  -