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DTSTART;TZID=Asia/Macau:20170412T110000
DTEND;TZID=Asia/Macau:20170412T120000
DTSTAMP:20260513T183941
CREATED:20170412T030056Z
LAST-MODIFIED:20220927T044403Z
UID:6089-1491994800-1491998400@www.fst.um.edu.mo
SUMMARY:The Comprehensive Language Knowledge Base and its development綜合型語言知識庫及其發展
DESCRIPTION:Instructors/Speakers\nProf. Yu Shiwen\nProfessor\nSchool of Electronics Engineering and Computer Science\nPeking University\nBeijing\nChina \nAbstract\n任何一個自然語言處理系統都需要一個適配的語言知識庫。北京大學計算語言學研究所積30年之努力，建成以《現代漢語語法資訊詞典》為基礎的綜合型語言知識庫。本報告介紹綜合型語言知識庫的主要內容及其發展。當前語言計算研究已深入到面向語言大資料的語義計算。詞彙、詞法、句法層面的語言知識庫對語言淺層分析技術的發展起到了至關重要的作用，這個成功的經驗對當前的語義計算研究有啟示意義。一項新的語義知識資源建設的任務是確定句子中的謂詞並標注其論元的語義角色。本報告介紹這項任務的概況，論述對這項語義知識資源工程的認知並初步總結參與這項工程的實踐經驗。 \nBiography\n俞士汶\, 男\, 1938年12月出生。北京大學資訊科學技術學院教授。1964年自北大計算數學專業畢業後一直在北大從事電腦學科的研究與教學工作。1986年起致力於計算語言學和自然語言處理的研究。作為第一完成人的主要研究成果有以《現代漢語語法資訊詞典》為基礎的“綜合型語言知識庫”，在獲得中國政府部門、中國全國性學術團體以及北京大學的多項獎勵後，於 2011年獲中國國家科學技術進步獎二等獎。同年獲中國中文資訊學會成立30年來首次頒發的終身成就獎。著作8本（其中2003年出版的《計算語言學概論》2016年獲評北京大學優秀教材），第一作者論文約110篇。作為博士生、碩士生的導師和博士後、訪問學者的合作教師，培養了一大批計算語言學領域的高端人才，於2012年獲北京大學訪問學者優秀導師榮譽。“綜合型語言知識庫”於2013年再次獲北京大學首屆產學研結合特別貢獻獎。當前參加中國國家重點基礎研究項目之973課題“融合三元空間的中文語言知識與世界知識獲取和組織”的研究工作。 \n 
URL:https://www.fst.um.edu.mo/event/the-comprehensive-language-knowledge-base-and-its-development/
LOCATION:E11-4045 (University of Macau)
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20170419T103000
DTEND;TZID=Asia/Macau:20170419T113000
DTSTAMP:20260513T183941
CREATED:20170419T023050Z
LAST-MODIFIED:20220927T044402Z
UID:6092-1492597800-1492601400@www.fst.um.edu.mo
SUMMARY:Numbers and Games\, Symmetry and Groups: My Life in Mathematics
DESCRIPTION:
URL:https://www.fst.um.edu.mo/event/numbers-and-games-symmetry-and-groups-my-life-in-mathematics/
LOCATION:E11-G015
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20170427T153000
DTEND;TZID=Asia/Macau:20170427T163000
DTSTAMP:20260513T183941
CREATED:20170427T073001Z
LAST-MODIFIED:20220927T044402Z
UID:6094-1493307000-1493310600@www.fst.um.edu.mo
SUMMARY:Motion trajectories for robotic task teaching
DESCRIPTION:Instructors/Speakers\nProf. You-Fu LI\nProfessor\nDepartment of Mechanical and Biomedical Engineering\nCity University of Hong Kong \nAbstract\nMotion trajectories play an important role in characterizing human or robot actions and behaviours. Effective ways to track and describe them are lacking that can fully depict spatial trajectories in 3D. In this work\, I will present our research in visual tracking and trajectory description. An invariant descriptor proposed for free form trajectory description in Euclidean space. The signature admits rich invariants due to the computational locality. By implementing the approximate signature\, the noise-sensitive high order derivatives are avoided. The trajectory can then be recognized based on the customized signatures similarity metric. Case studies will be given to show the signature’s effectiveness and robustness in 3-D trajectory description and recognition. \nBiography\nYou-Fu Li received the PhD degree in robotics from the Department of Engineering Science\, University of Oxford in 1993. From 1993 to 1995 he was a research staff in the Department of Computer Science at the University of Wales\, Aberystwyth\, UK. He joined City University of Hong Kong in 1995 and is currently professor in the Department of Mechanical and Biomedical Engineering. His research interests include robot sensing\, robot vision\, and visual tracking. He has served as an Associate Editor for IEEE Transactions on Automation Science and Engineering (T-ASE)\, Associate Editor and Guest Editor for IEEE Robotics and Automation Magazine (RAM)\, and Editor for CEB\, IEEE International Conference on Robotics and Automation (ICRA). \n 
URL:https://www.fst.um.edu.mo/event/motion-trajectories-for-robotic-task-teaching/
LOCATION:E11-1012
CATEGORIES:eme_events,event_list,seminarslectures
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