Learning Knowledge Bases for Multimedia in 2015
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Description
Knowledge acquisition, representation, and reasoning has been one of the long-standing challenges in artificial intelligence 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 knowledge bases is becoming a...[Show more]
dc.contributor.author | Xie, Lexing | |
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dc.contributor.author | Wang, Haixun | |
dc.coverage.spatial | Brisbane, Australia | |
dc.date.accessioned | 2016-06-14T23:21:14Z | |
dc.date.created | October 26-30, 2015 | |
dc.identifier.isbn | 9781450334594 | |
dc.identifier.uri | http://hdl.handle.net/1885/103786 | |
dc.description.abstract | Knowledge acquisition, representation, and reasoning has been one of the long-standing challenges in artificial intelligence 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 knowledge bases is becoming a lively fusion area among web in- formation extraction, machine learning, databases and information retrieval, with knowledge over images and multimedia 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 representation, 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 | |
dc.publisher | Association for Computing Machinery (ACM) | |
dc.relation.ispartofseries | 23rd ACM International Conference on Multimedia MM'15 | |
dc.source | Learning Knowledge Bases for Multimedia in 2015 | |
dc.title | Learning Knowledge Bases for Multimedia in 2015 | |
dc.type | Conference paper | |
local.description.notes | Imported from ARIES | |
local.description.refereed | Yes | |
dc.date.issued | 2015 | |
local.identifier.absfor | 080107 - Natural Language Processing | |
local.identifier.ariespublication | u4334215xPUB1512 | |
local.type.status | Published Version | |
local.contributor.affiliation | Xie, Lexing, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Wang, Haixun, Facebook Inc. | |
local.description.embargo | 2037-12-31 | |
local.bibliographicCitation.startpage | 1323 | |
local.bibliographicCitation.lastpage | 1324 | |
local.identifier.doi | 10.1145/2733373.2807418 | |
local.identifier.absseo | 970108 - Expanding Knowledge in the Information and Computing Sciences | |
dc.date.updated | 2016-06-14T09:03:18Z | |
local.identifier.scopusID | 2-s2.0-84962787259 | |
Collections | ANU Research Publications |
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