Research on Summary Sentences Extraction Oriented to Chinese Patent
Lei Wang, Xueqiang Lv, Xindong You
Available Online April 2019.
- https://doi.org/10.2991/icmeit-19.2019.61How to use a DOI?
- Chinese patent summarization; learning to rank; semantic weigh; word2vec.
- 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.
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 -