Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey is a research paper published in Multimedia Tools and Applications (2019). On theSindex it has a DataRank of 1.1. It has been cited 1,892 times.
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Linked data & code
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Base Score Contribution
1.1
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →National Natural Science Foundation of China under Grant
Grant: 61170035
FWCI
66.19
Citation Percentile
1.0%
Influential Citations
61
Citation Trend
Fields of Study
Keywords
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Additional file 1 of Enhancing engagement beyond the conference walls: analysis of Twitter use at #ICPIC2019 infection prevention and control conference
Additional file 1 of Temporal topic model for clinical pathway mining from electronic medical records
Additional file 1 of Temporal topic model for clinical pathway mining from electronic medical records
Additional file 1 of Data-mining analysis of media frame effects on social perception of schizophrenia renaming in Korea
Additional file 4 of Data-mining analysis of media frame effects on social perception of schizophrenia renaming in Korea
Additional file 1 of Data-mining analysis of media frame effects on social perception of schizophrenia renaming in Korea
Additional file 3 of Data-mining analysis of media frame effects on social perception of schizophrenia renaming in Korea
Additional file 2 of Data-mining analysis of media frame effects on social perception of schizophrenia renaming in Korea
Additional file 3 of Data-mining analysis of media frame effects on social perception of schizophrenia renaming in Korea
Additional file 4 of Data-mining analysis of media frame effects on social perception of schizophrenia renaming in Korea
Additional file 2 of Data-mining analysis of media frame effects on social perception of schizophrenia renaming in Korea