What is wrong with topic modeling? And how to fix it using search-based software engineering
Topic modeling finds human-readable structures in unstructured textual data. A widely used topic modeling technique is Latent Dirichlet allocation. When running on different datasets, LDA suffers from “order effects”, i.e., different topics are generated if the order of training data is shuffled. Su...
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Published in | Information and software technology Vol. 98; pp. 74 - 88 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.06.2018
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Subjects | |
Online Access | Get full text |
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