學術產出-會議論文

文章檢視/開啟

書目匯出

Google ScholarTM

政大圖書館

引文資訊

TAIR相關學術產出

題名 Leveraging morpho-semantics for the discovery of relations in Chinese wordnet
作者 張瑜芸
Chang, Yu-Yun
Hsieh, Shu-Kai
貢獻者 語言所
日期 2014-01
上傳時間 17-十二月-2020 09:03:28 (UTC+8)
摘要 Semantic relations of different types have played an important role in wordnet, and have been widely recognized in various fields. In recent years, with the growing interests of constructing semantic network in support of intelligent systems, automatic semantic relation discovery has become an urgent task. This paper aims to extract semantic relations relying on the in situ morpho-semantic structure in Chinese which can dispense of an outside source such as corpus or web data. Manual evaluation of thousands of word pairs shows that most relations can be successful predicted. We believe that it can serve as a valuable starting point in complementing with other approaches, which will hold promise for the robust lexical relations acquisition.
關聯 Proceedings of the Seventh Global Wordnet Conference, University of Tartu Press, pp.283-289
資料類型 conference
dc.contributor 語言所
dc.creator (作者) 張瑜芸
dc.creator (作者) Chang, Yu-Yun
dc.creator (作者) Hsieh, Shu-Kai
dc.date (日期) 2014-01
dc.date.accessioned 17-十二月-2020 09:03:28 (UTC+8)-
dc.date.available 17-十二月-2020 09:03:28 (UTC+8)-
dc.date.issued (上傳時間) 17-十二月-2020 09:03:28 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/133012-
dc.description.abstract (摘要) Semantic relations of different types have played an important role in wordnet, and have been widely recognized in various fields. In recent years, with the growing interests of constructing semantic network in support of intelligent systems, automatic semantic relation discovery has become an urgent task. This paper aims to extract semantic relations relying on the in situ morpho-semantic structure in Chinese which can dispense of an outside source such as corpus or web data. Manual evaluation of thousands of word pairs shows that most relations can be successful predicted. We believe that it can serve as a valuable starting point in complementing with other approaches, which will hold promise for the robust lexical relations acquisition.
dc.format.extent 255177 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) Proceedings of the Seventh Global Wordnet Conference, University of Tartu Press, pp.283-289
dc.title (題名) Leveraging morpho-semantics for the discovery of relations in Chinese wordnet
dc.type (資料類型) conference