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Topic Modeling for Analyzing Topic Manipulation Skills [PDF]
Information, 2021 There are many ways to communicate with people, the most representative of which is a conversation. A smooth conversation should not only be written in a grammatically appropriate manner, but also deal with the subject of conversation; this is known as language ability.
Seok-Ju Hwang +4 more
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Combined models for topic spotting and topic-dependent language modeling [PDF]
1997 IEEE Workshop on Automatic Speech Recognition and Understanding Proceedings, 2002 A new statistical method for Language Modeling and spoken document classification is proposed. It is based on a mixture of topic dependent probabilities. Each topic dependent probability is in turn a mixture of n-gram probabilities and the probability of Kullback-Lieber (KL) distances between keyword unigrams and distribution obtained from the content ...
Bigi, Brigitte +3 more
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Polylingual topic models [PDF]
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing Volume 2 - EMNLP '09, 2009 Topic models are a useful tool for analyzing large text collections, but have previously been applied in only monolingual, or at most bilingual, contexts. Meanwhile, massive collections of interlinked documents in dozens of languages, such as Wikipedia, are now widely available, calling for tools that can characterize content in many languages.
Mimno, David +4 more
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A Topic Coverage Approach to Evaluation of Topic Models [PDF]
IEEE Access, 2021 Topic models are widely used unsupervised models capable of learning topics - weighted lists of words and documents - from large collections of text documents. When topic models are used for discovery of topics in text collections, a question that arises naturally is how well the model-induced topics correspond to topics of interest to the analyst.
Damir Korencic +3 more
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TOMODAPI: A Topic Modeling API to Train, Use and Compare Topic Models [PDF]
Proceedings of Second Workshop for NLP Open Source Software (NLP-OSS), 2020 From LDA to neural models, different topic modeling approaches have been proposed in the literature. However, their suitability and performance is not easy to compare, particularly when the algorithms are being used in the wild on heterogeneous datasets.
Lisena, Pasquale +3 more
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Differential Topic Models [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015 In applications we may want to compare different document collections: they could have shared content but also different and unique aspects in particular collections. This task has been called comparative text mining or cross-collection modeling.
Chen, Changyou +4 more
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Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022 We propose a new problem called coordinated topic modeling that imitates human behavior while describing a text corpus. It considers a set of well-defined topics like the axes of a semantic space with a reference representation. It then uses the axes to model a corpus for easily understandable representation. This new task helps represent a corpus more
Akash, Pritom Saha +2 more
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A Query-Driven Topic Model [PDF]
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 2021 Topic modeling is an unsupervised method for revealing the hidden semantic structure of a corpus. It has been increasingly widely adopted as a tool in the social sciences, including political science, digital humanities and sociological research in general.
Rob Procter, Zheng Fang, Yulan He
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A network approach to topic models [PDF]
Science Advances, 2018 A new approach to topic models finds topics through community detection in word-document networks.
Eduardo G. Altmann +4 more
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