کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4947721 1439591 2017 29 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
MLLDA: Multi-level LDA for modelling users on content curation social networks
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
MLLDA: Multi-level LDA for modelling users on content curation social networks
چکیده انگلیسی
User analysis is an important part of social network analysis. Most existing studies model users separately using either user-generated contents or social links among users. In this paper we propose to model users on the Content Curation Social Network (CCSN) in a unified framework by mining user-generated contents as well as social links. We propose a latent Bayesian model Multi-level LDA (MLLDA) that represents users with latent user interests discovered from user-contributed textual description and social links formed by information sharing. We demonstrate that MLLDA can produce accurate user models for community discovery and recommendation on the CCSN.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 236, 2 May 2017, Pages 73-81
نویسندگان
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