Interspeech 2018 2018
DOI: 10.21437/interspeech.2018-1100
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Play Duration Based User-Entity Affinity Modeling in Spoken Dialog System

Abstract: Multimedia streaming services over spoken dialog systems have become ubiquitous. User-entity affinity modeling is critical for the system to understand and disambiguate user intents and personalize user experiences. However, fully voice-based interaction demands quantification of novel behavioral cues to determine user affinities. In this work, we propose using play duration cues to learn a matrix factorization based collaborative filtering model. We first binarize play durations to obtain implicit positive an… Show more

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“…Different variants of matrix factorization methods have been proposed such as non-negative matrix factorization (Zhang et al, 2006 ), SVD++ (Koren, 2008 ), timeSVD++ (Koren, 2009 ), and factorization machines (Rendle, 2010 ). Xiao et al ( 2018 ) proposed a matrix factorization model for recommending music in IPAs. To cope with the limitation of VUI, they binarize play durations to obtain implicit affinity labels.…”
Section: Related Workmentioning
confidence: 99%
“…Different variants of matrix factorization methods have been proposed such as non-negative matrix factorization (Zhang et al, 2006 ), SVD++ (Koren, 2008 ), timeSVD++ (Koren, 2009 ), and factorization machines (Rendle, 2010 ). Xiao et al ( 2018 ) proposed a matrix factorization model for recommending music in IPAs. To cope with the limitation of VUI, they binarize play durations to obtain implicit affinity labels.…”
Section: Related Workmentioning
confidence: 99%