Results 71 to 80 of about 25,541,881 (369)
Bibliographic Analysis on Research Publications using Authors, Categorical Labels and the Citation Network [PDF]
, 2016 Bibliographic analysis considers the author's research areas, the citation network and the paper content among other things. In this paper, we combine these three in a topic model that produces a bibliographic model of authors, topics and documents ...
Buntine, Wray, Lim, Kar Wai
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Visualizing Topic Uncertainty in Topic Modelling
, 2023 Word clouds became a standard tool for presenting results of natural language processing methods such as topic modelling. They exhibit most important words, where word size is often chosen proportional to the relevance of words within a topic. In the latent Dirichlet allocation (LDA) model, word clouds are graphical presentations of a vector of weights
openaire +3 more sources
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
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Sequential Topic Selection Model with Latent Variable for Topic-Grounded Dialogue [PDF]
arXiv, 2022 Recently, topic-grounded dialogue system has attracted significant attention due to its effectiveness in predicting the next topic to yield better responses via the historical context and given topic sequence. However, almost all existing topic prediction solutions focus on only the current conversation and corresponding topic sequence to predict the ...
arxiv
Correction: A correlated topic model of Science
, 2007 Correction to Annals of Applied Statistics 1 (2007) 17--35 [doi:10.1214/07-AOAS114]Comment: Published in at http://dx.doi.org/10.1214/07-AOAS136 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical ...
Blei, David M., Lafferty, John D.
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Learning Topic Models - Going beyond SVD [PDF]
, 2012 Topic Modeling is an approach used for automatic comprehension and classification of data in a variety of settings, and perhaps the canonical application is in uncovering thematic structure in a corpus of documents. A number of foundational works both in
Arora, Sanjeev, Ge, Rong, Moitra, Ankur
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Topic Taxonomy Expansion via Hierarchy-Aware Topic Phrase Generation [PDF]
arXiv, 2022 Topic taxonomies display hierarchical topic structures of a text corpus and provide topical knowledge to enhance various NLP applications. To dynamically incorporate new topic information, several recent studies have tried to expand (or complete) a topic taxonomy by inserting emerging topics identified in a set of new documents.
arxiv
A Correlated Topic Model Using Word Embeddings
International Joint Conference on Artificial Intelligence, 2017 Conventional correlated topic models are able to capture correlation structure among latent topics by replacing the Dirichlet prior with the logistic normal distribution.
Guangxu Xun +4 more
semanticscholar +1 more source
Evaluation methods for topic models [PDF]
Proceedings of the 26th Annual International Conference on Machine Learning, 2009 A natural evaluation metric for statistical topic models is the probability of held-out documents given a trained model. While exact computation of this probability is intractable, several estimators for this probability have been used in the topic modeling literature, including the harmonic mean method and empirical likelihood method.
Wallach, Hanna M. +3 more
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Dendritic cells steering antigen and leukocyte traffic in lymph nodes
FEBS Letters, EarlyView.Dendritic cells are key players in the activation of T cells and their commitment to effector function. In this In a Nutshell Review, we will discuss how dendritic cells guide the trafficking of antigen and leukocytes in the lymph node, thus influencing T‐cell activation processes. Dendritic cells (DCs) play a central role in initiating and shaping the
Enrico Dotta +3 more
wiley +1 more source