Semantically-Enhanced Topic Modeling

Author:

Viegas Felipe1,Luiz Washington1,Gomes Christian2,Khatibi Amir1,Canuto Sérgio3,Mourão Fernando4,Salles Thiago1,Rocha Leonardo2,Gonçalves Marcos André1

Affiliation:

1. Federal University of Minas Gerais, Belo Horizonte, Brazil

2. Federal University of São João del Rei, São João del Rei, Brazil

3. Federal Institute of Goias, Goias, Brazil

4. Seek AI Labs, Belo Horizonte, Brazil

Funder

Fapemig

Astrein

InWeb

CNPq

CAPES

Finep

Mundiale

MASWeb

Publisher

ACM

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. On the Role of Semantic Word Clusters — CluWords — in Natural Language Processing (NLP) Tasks;Anais do XXXVII Concurso de Teses e Dissertações (CTD 2024);2024-07-21

2. Evaluating Topic Modeling Pre-processing Pipelines for Portuguese Texts;Brazilian Symposium on Multimedia and Web;2022-11-07

3. Correlating Historical Events and Cinematic Releases Using Web Information;Brazilian Symposium on Multimedia and Web;2022-11-07

4. Accurate Context Extraction from Unstructured Text Based on Deep Learning;2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT);2022-11

5. Latent Semantic Indexing (LSI) and Hierarchical Dirichlet Process (HDP) Models on News Data;2022 5th International Conference of Computer and Informatics Engineering (IC2IE);2022-09-13

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