Results 61 to 70 of about 810,432 (208)
Neurocomputing, 2023 Nonnegative matrix factorization (NMF) based topic modeling methods do not rely on model- or data-assumptions much. However, they are usually formulated as difficult optimization problems, which may suffer from bad local minima and high computational complexity.
Jianyu Wang, Xiao-Lei Zhang 0001
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Applied Sciences, 2022 The personalized recommendation system is a useful tool adopted by e-retailers to help consumers to find items in line with their preferences. Existing methods focus on learning user preferences from a user-item matrix or online reviews after purchasing,
Xin Huang, Xiaojuan Liu
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CoRR, 2016 We develop a privatised stochastic variational inference method for Latent Dirichlet Allocation (LDA). The iterative nature of stochastic variational inference presents challenges: multiple iterations are required to obtain accurate posterior distributions, yet each iteration increases the amount of noise that must be added to achieve a reasonable ...
Park, M. +3 more
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Topic Intrusion for Automatic Topic Model Evaluation [PDF]
, 2020 Topic coherence is increasingly being used to evaluate topic models and filter topics for enduser applications. Topic coherence measures how well topic words relate to each other, but offers little insight into the utility of the topics in describing the
Lau, JH, Baldwin, T, Bhatia, S
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Topic Balancing with Additive Regularization of Topic Models [PDF]
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, 2020 This article proposes a new approach for building topic models on unbalanced collections in topic modelling, based on the existing methods and our experiments with such methods. Real-world data collections contain topics in various proportions, and often documents of the relatively small theme become distributed all over the larger topics instead of ...
Eugenia Veselova +1 more
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mSystems, 2020 Gut dysbiosis has been repeatedly reported in Parkinson’s disease (PD) but only once in idiopathic rapid-eye-movement sleep behavior disorder (iRBD) from Germany.
Hiroshi Nishiwaki +13 more
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Model-Parallel Inference for Big Topic Models
, 2018 In real world industrial applications of topic modeling, the ability to capture gigantic conceptual space by learning an ultra-high dimensional topical representation, i.e., the so-called "big model", is becoming the next desideratum after enthusiasms on
Jin Kyu Kim (5364002) +3 more
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Modeling the evolution of development topics using Dynamic Topic Models [PDF]
2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER), 2015 As the development of a software project progresses, its complexity grows accordingly, making it difficult to understand and maintain. During software maintenance and evolution, software developers and stakeholders constantly shift their focus between different tasks and topics.
Jiajun Hu +3 more
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Identify Topic Relations in Scientific Literature Using Topic Modeling
, 2020 IEEE Over the past five years, topic models have been applied to bibliometrics research as an efficient tool for discovering latent and potentially useful content.
Wang, X +7 more
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CoRR, 2016 Recently there has been significant activity in developing algorithms with provable guarantees for topic modeling. In standard topic models, a topic (such as sports, business, or politics) is viewed as a probability distribution $\vec a_i$ over words, and a document is generated by first selecting a mixture $\vec w$ over topics, and then generating ...
Avrim Blum, Nika Haghtalab
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