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Contextual Wisdom: Social Relations and Correlations for Multimedia Event Annotation

Zunjarwad, Amit; Sundaram, Hari; Xie, Lexing

Description

This work deals with the problem of event annotation in social networks. The problem is made difficult due to variability of semantics and due to scarcity of labeled data. Events refer to real-world phenomena that occur at a specific time and place, and media and text tags are treated as facets of the event metadata. We are proposing a novel mechanism for event annotation by leveraging related sources (other annotators) in a social network. Our approach exploits event concept similarity,...[Show more]

dc.contributor.authorZunjarwad, Amit
dc.contributor.authorSundaram, Hari
dc.contributor.authorXie, Lexing
dc.coverage.spatialAugsburg Germany
dc.date.accessioned2015-12-10T22:41:26Z
dc.date.createdSeptember 24-29 2007
dc.identifier.isbn9781595937018
dc.identifier.urihttp://hdl.handle.net/1885/57907
dc.description.abstractThis work deals with the problem of event annotation in social networks. The problem is made difficult due to variability of semantics and due to scarcity of labeled data. Events refer to real-world phenomena that occur at a specific time and place, and media and text tags are treated as facets of the event metadata. We are proposing a novel mechanism for event annotation by leveraging related sources (other annotators) in a social network. Our approach exploits event concept similarity, concept co-occurrence and annotator trust. We compute concept similarity measures across all facets. These measures are then used to compute event-event and user-user activity correlation. We compute inter-facet concept co-occurrence statistics from the annotations by each user. The annotator trust is determined by first requesting the trusted annotators (seeds) from each user and then propagating the trust amongst the social network using the biased PageRank algorithm. For a specific media instance to be annotated, we start the process from an initial query vector and the optimal recommendations are determined by using a coupling strategy between the global similarity matrix, and the trust weighted global co-occurrence matrix. The coupling links the common shared knowledge (similarity between concepts) that exists within the social network with trusted and personalized observations (concept co-occurrences). Our initial experiments on annotated everyday events are promising and show substantial gains against traditional SVM based techniques.
dc.publisherAssociation for Computing Machinery Inc (ACM)
dc.relation.ispartofseriesACM Multimedia 2007
dc.sourceProceedings of ACM Multimedia 2007
dc.source.urihttp://mmc36.informatik.uni-augsburg.de/acmmm2007/
dc.subjectKeywords: Content management; Event annotation; Labeled data; PageRank algorithm; Algorithms; Real time systems; Statistics; User interfaces; Multimedia systems Content management; Context; Event annotation; Images; Multimedia; Social networks
dc.titleContextual Wisdom: Social Relations and Correlations for Multimedia Event Annotation
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2007
local.identifier.absfor080199 - Artificial Intelligence and Image Processing not elsewhere classified
local.identifier.absfor080609 - Information Systems Management
local.identifier.absfor080109 - Pattern Recognition and Data Mining
local.identifier.ariespublicationU3594520xPUB420
local.type.statusPublished Version
local.contributor.affiliationZunjarwad, Amit, Arizona State University
local.contributor.affiliationSundaram, Hari, Arizona State University
local.contributor.affiliationXie, Lexing, College of Engineering and Computer Science, ANU
local.description.embargo2037-12-31
local.identifier.doi10.1145/1291233.1291382
local.identifier.absseo890301 - Electronic Information Storage and Retrieval Services
local.identifier.absseo810105 - Intelligence
local.identifier.absseo950205 - Visual Communication
dc.date.updated2015-12-09T11:07:47Z
local.identifier.scopusID2-s2.0-37849006793
CollectionsANU Research Publications

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