Results 41 to 50 of about 23,460 (215)
Leveraging Global and Local Topic Popularities for LDA-Based Document Clustering
IEEE Access, 2020 Document clustering is of high importance for many natural language technologies. A wide range of computational traditional topic models, such as LDA (Latent Dirichlet Allocation) and its variants, have made great progress. However, traditional LDA-based
Peng Yang, Yu Yao, Huajian Zhou
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A Microblog Hot Topic Mining Method Integrating Tag Semantics [PDF]
Jisuanji gongcheng, 2019 Due to the short length of the microblog text,the direct use of Latent Dirichlet Allocation(LDA) model will lead to high-dimensional sparse feature vectors.Thus,a hot topic mining method integrating tag semantics is proposed.The common block algorithm is
ZHOU Fuxing, CHEN Xiuzhen, MA Jin, LI Shenghong
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Multi-angle Personalized Microblog Recommendation Algorithm Based on LDA Model [PDF]
Jisuanji gongcheng, 2017 Using Latent Dirichlet Allocation(LDA) to mine topics which users are interested in is the most popular topic-mining method.In order to improve users′ experience and recommend fresh microblog which users are interested,this paper puts forward a multi ...
SUN Yujie,QIN Yongbin
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Extending Information Retrieval Methods to Personalized Genomic-Based Studies of Disease
Cancer Informatics, 2014 Genomic-based studies of disease now involve diverse types of data collected on large groups of patients. A major challenge facing statistical scientists is how best to combine the data, extract important features, and comprehensively characterize the ...
Shuyun Ye +2 more
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Journal of the Association for Information Science and Technology, EarlyView.Abstract Context‐centric proactive information delivery (PID) is a relatively underexplored domain within recommender systems (RS) aimed at enhancing Knowledge Workers' productivity by proactively providing relevant information during digital tasks.
Mahta Bakhshizadeh +4 more
wiley +1 more source
A Topic Modeling Toolbox Using Belief Propagation [PDF]
, 2012 Latent Dirichlet allocation (LDA) is an important hierarchical Bayesian model for probabilistic topic modeling, which attracts worldwide interests and touches on many important applications in text mining, computer vision and computational biology.
Zeng, Jia
core
Delineating gender/sex‐related studies through bibliometric analysis
Journal of the Association for Information Science and Technology, EarlyView.Abstract The multidisciplinary and socially grounded nature of Women's/Gender/Feminist Studies poses unique challenges for bibliometric analysis, as it extends beyond conventional disciplinary boundaries. This paper makes three key contributions: (1) We propose a novel retrieval method for constructing a corpus of scholarly documents in research areas ...
Natsumi S. Shokida +2 more
wiley +1 more source
An Empirical Study of Stochastic Variational Algorithms for the Beta Bernoulli Process [PDF]
, 2015 Stochastic variational inference (SVI) is emerging as the most promising candidate for scaling inference in Bayesian probabilistic models to large datasets.
Ghahramani, Zoubin +2 more
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A correlated topic model of Science
, 2007 Topic models, such as latent Dirichlet allocation (LDA), can be useful tools for the statistical analysis of document collections and other discrete data. The LDA model assumes that the words of each document arise from a mixture of topics, each of which
Blei, David M., Lafferty, John D.
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A derivation of variational message passing (VMP) for latent Dirichlet allocation (LDA)
, 2021 24 pages,not yet submitted ...
Taylor, Rebecca M. C. +2 more
openaire +2 more sources