TY - GEN
T1 - Learning knowledge bases for multimedia in 2015
AU - Xie, Lexing
AU - Wang, Haixun
N1 - Publisher Copyright:
© 2015 ACM.
PY - 2015/10/13
Y1 - 2015/10/13
N2 - Knowledge acquisition, representation, and reasoning has been one of the long-standing challenges in arti-cial intelli-gence and related application areas. Only in the past few years, massive amounts of structured and semi-structured data that directly or indirectly encode human knowledge be-came widely available, turning the knowledge representation problems into a computational grand challenge with feasible solutions in sight. The research and development on knowl-edge bases is becoming a lively fusion area among web in-formation extraction, machine learning, databases and infor-mation retrieval, with knowledge over images and multime-dia emerging as another new frontier of representation and acquisition. This tutorial aims to present a gentle overview of knowledge bases on text and multimedia, including rep-resentation, acquisition, and inference. In particular, the 2015 edition of the tutorial will include recent progress from several active research communities: web, natural language processing, and computer vision and multimedia.
AB - Knowledge acquisition, representation, and reasoning has been one of the long-standing challenges in arti-cial intelli-gence and related application areas. Only in the past few years, massive amounts of structured and semi-structured data that directly or indirectly encode human knowledge be-came widely available, turning the knowledge representation problems into a computational grand challenge with feasible solutions in sight. The research and development on knowl-edge bases is becoming a lively fusion area among web in-formation extraction, machine learning, databases and infor-mation retrieval, with knowledge over images and multime-dia emerging as another new frontier of representation and acquisition. This tutorial aims to present a gentle overview of knowledge bases on text and multimedia, including rep-resentation, acquisition, and inference. In particular, the 2015 edition of the tutorial will include recent progress from several active research communities: web, natural language processing, and computer vision and multimedia.
KW - Knowledge Graph
KW - Learning.
KW - Multimedia
UR - https://www.scopus.com/pages/publications/84962787259
U2 - 10.1145/2733373.2807418
DO - 10.1145/2733373.2807418
M3 - Conference Paper
T3 - MM 2015 - Proceedings of the 2015 ACM Multimedia Conference
SP - 1323
EP - 1324
BT - MM 2015 - Proceedings of the 2015 ACM Multimedia Conference
PB - Association for Computing Machinery (ACM)
T2 - 23rd ACM International Conference on Multimedia, MM 2015
Y2 - 26 October 2015 through 30 October 2015
ER -