Open Research

Probabilistic Latent Maximal Marginal Relevance

dc.contributor.author	Guo, Shengbo
dc.contributor.author	Sanner, Scott
dc.coverage.spatial	Geneva Switzerland
dc.date.accessioned	2015-12-08T22:22:01Z
dc.date.created	July 19 2010
dc.identifier.isbn	9781450301534
dc.identifier.uri	http://hdl.handle.net/1885/32382
dc.publisher	Association for Computing Machinery Inc (ACM)
dc.relation.ispartofseries	International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2010)
dc.source	Proceedings of International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2010)
dc.subject	Keywords: Diversity; Diversity metrics; GraphicaL model; Latent semantic indexing; Latent variable; Maximal Marginal Relevance; Objective criteria; Probabilistic inference; Recommender systems; Similarity metrics; Term Frequency; Graphic methods; Information retrie Diversity; Graphical models; Maximal Marginal Relevance
dc.title	Probabilistic Latent Maximal Marginal Relevance
dc.type	Conference paper
local.description.notes	Imported from ARIES
local.description.refereed	Yes
dc.date.issued	2010
local.identifier.absfor	080199 - Artificial Intelligence and Image Processing not elsewhere classified
local.identifier.ariespublication	u4963866xPUB91
local.type.status	Published Version
local.contributor.affiliation	Guo, Shengbo, College of Engineering and Computer Science, ANU
local.contributor.affiliation	Sanner, Scott, College of Engineering and Computer Science, ANU
local.description.embargo	2037-12-31
local.bibliographicCitation.startpage	2
local.identifier.doi	10.1145/1835449.1835639
local.identifier.absseo	890299 - Computer Software and Services not elsewhere classified
dc.date.updated	2016-06-14T09:10:12Z
local.identifier.scopusID	2-s2.0-77956042078
Collections	ANU Research Publications

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