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Learning Knowledge Bases for Multimedia in 2015

Xie, Lexing; Wang, Haixun

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.authorXie, Lexing
dc.contributor.authorWang, Haixun
dc.coverage.spatialBrisbane, Australia
dc.date.accessioned2016-06-14T23:21:14Z
dc.date.createdOctober 26-30, 2015
dc.identifier.isbn9781450334594
dc.identifier.urihttp://hdl.handle.net/1885/103786
dc.description.abstractKnowledge 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.publisherAssociation for Computing Machinery (ACM)
dc.relation.ispartofseries23rd ACM International Conference on Multimedia MM'15
dc.sourceLearning Knowledge Bases for Multimedia in 2015
dc.titleLearning Knowledge Bases for Multimedia in 2015
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2015
local.identifier.absfor080107 - Natural Language Processing
local.identifier.ariespublicationu4334215xPUB1512
local.type.statusPublished Version
local.contributor.affiliationXie, Lexing, College of Engineering and Computer Science, ANU
local.contributor.affiliationWang, Haixun, Facebook Inc.
local.description.embargo2037-12-31
local.bibliographicCitation.startpage1323
local.bibliographicCitation.lastpage1324
local.identifier.doi10.1145/2733373.2807418
local.identifier.absseo970108 - Expanding Knowledge in the Information and Computing Sciences
dc.date.updated2016-06-14T09:03:18Z
local.identifier.scopusID2-s2.0-84962787259
CollectionsANU Research Publications

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