Results 81 to 90 of about 63,472 (294)
Stochastic Divergence Minimization for Biterm Topic Model
, 2017 As the emergence and the thriving development of social networks, a huge number of short texts are accumulated and need to be processed. Inferring latent topics of collected short texts is useful for understanding its hidden structure and predicting new ...
Cui, Zhenghang +2 more
core +1 more source
Inference in Supervised latent Dirichlet allocation [PDF]
2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011 Supervised latent Dirichlet allocation (Supervised-LDA) [1] is a probabilistic topic model that can be used for classification. One of the advantages of Supervised-LDA over unsupervised LDA is that it can potentially learn topics that are inline with the class label.
Balaji Lakshminarayanan, Raviv Raich
openaire +1 more source
Business Strategy and the Environment, EarlyView.ABSTRACT This study examines how European automotive companies disclose circular economy (CE) information in light of the Corporate Sustainability Reporting Directive (CSRD) and the European Sustainability Reporting Standards (ESRS) E5. Using a mixed‐methods, data‐driven approach that combines keyword analysis and latent Dirichlet allocation (LDA ...
Dominika Hadro +4 more
wiley +1 more source
Aurora Image Classification Based on Multi-Feature Latent Dirichlet Allocation
Remote Sensing, 2018 Due to the rich physical meaning of aurora morphology, the classification of aurora images is an important task for polar scientific expeditions. However, the traditional classification methods do not make full use of the different features of aurora ...
Yanfei Zhong +4 more
doaj +1 more source
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2021 Recently, Sentiment Analysis is used for expression detection of products or services. Sentiment Analysis is one category type with a level of aspect focused on extracting product aspects.
Dinda Adimanggala +2 more
doaj +1 more source
Unsupervised Terminological Ontology Learning based on Hierarchical Topic Modeling
, 2017 In this paper, we present hierarchical relationbased latent Dirichlet allocation (hrLDA), a data-driven hierarchical topic model for extracting terminological ontologies from a large number of heterogeneous documents.
Bless, Patrick +2 more
core +1 more source
Harnessing Generative AI for Sustainable Supply Chains: Lean, Circular and Green Perspectives
Business Strategy and the Environment, EarlyView.ABSTRACT Generative artificial intelligence is playing a significant role in the transformation of digital ecosystems by reinventing the processes of content generation, process automation, product innovation and customer experience. At the same time that these technologies are becoming more integrated into routine operations, the focus has shifted to ...
Ashutosh Singh +3 more
wiley +1 more source
Partial Membership Latent Dirichlet Allocation
, 2015 cut to 6 pages, add sunset ...
Chen, Chao, Zare, Alina, Cobb, J. Tory
openaire +2 more sources
Bayesian clustering of multivariate extremes
Canadian Journal of Statistics, EarlyView.Abstract The asymptotic dependence structure between multivariate extreme values is fully characterized by their projections on the unit simplex. Under mild conditions, the only constraint on the resulting distributions is that their marginal means must be equal, which results in a nonparametric model that can be difficult to use in applications ...
Sonia Alouini, Anthony C. Davison
wiley +1 more source
Practical Collapsed Stochastic Variational Inference for the HDP [PDF]
, 2013 Recent advances have made it feasible to apply the stochastic variational paradigm to a collapsed representation of latent Dirichlet allocation (LDA).
Bleier, Arnim
core