{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T19:34:58Z","timestamp":1777491298622,"version":"3.51.4"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,8]]},"abstract":"<jats:p>Sememes are defined as the minimum semantic units of human languages. People have manually annotated lexical sememes for words and form linguistic knowledge bases. However, manual construction is time-consuming and labor-intensive, with significant annotation inconsistency and noise. In this paper, we for the first time explore to automatically predict lexical sememes based on semantic meanings of words encoded by word embeddings. Moreover, we apply matrix factorization to learn semantic relations between sememes and words. In experiments, we take a real-world sememe knowledge base HowNet for training and evaluation, and the results reveal the effectiveness of our method for lexical sememe prediction. Our method will be of great use for annotation verification of existing noisy sememe knowledge bases and annotation suggestion of new words and phrases.<\/jats:p>","DOI":"10.24963\/ijcai.2017\/587","type":"proceedings-article","created":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T05:14:07Z","timestamp":1501218847000},"page":"4200-4206","source":"Crossref","is-referenced-by-count":21,"title":["Lexical Sememe Prediction via Word Embeddings and Matrix Factorization"],"prefix":"10.24963","author":[{"given":"Ruobing","family":"Xie","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, State Key Lab on Intelligent Technology and Systems, National Lab for Information Science and Technology, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingchi","family":"Yuan","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, State Key Lab on Intelligent Technology and Systems, National Lab for Information Science and Technology, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiyuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, China"},{"name":"Jiangsu Collaborative Innovation Center for Language Ability, Jiangsu Normal University, Xuzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maosong","family":"Sun","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China"},{"name":"Jiangsu Collaborative Innovation Center for Language Ability, Jiangsu Normal University, Xuzhou 221009 China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"name":"Twenty-Sixth International Joint Conference on Artificial Intelligence","theme":"Artificial Intelligence","location":"Melbourne, Australia","acronym":"IJCAI-2017","number":"26","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)","University of Technology Sydney (UTS)","Australian Computer Society (ACS)"],"start":{"date-parts":[[2017,8,19]]},"end":{"date-parts":[[2017,8,26]]}},"container-title":["Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T07:54:39Z","timestamp":1501228479000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2017\/587"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2017,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2017\/587","relation":{},"subject":[],"published":{"date-parts":[[2017,8]]}}}