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  4. Cited By
Language Modeling by Clustering with Word Embeddings for Text
  Readability Assessment

Language Modeling by Clustering with Word Embeddings for Text Readability Assessment

5 September 2017
Miriam Cha
Youngjune Gwon
H. T. Kung
ArXiv (abs)PDFHTML

Papers citing "Language Modeling by Clustering with Word Embeddings for Text Readability Assessment"

10 / 10 papers shown
Strategies for Arabic Readability Modeling
Strategies for Arabic Readability Modeling
Juan David Pineros Liberato
Bashar Alhafni
Muhamed Al Khalil
Nizar Habash
201
5
0
03 Jul 2024
Cross-corpus Readability Compatibility Assessment for English Texts
Cross-corpus Readability Compatibility Assessment for English TextsIEEE Access (IEEE Access), 2023
Zhenzhen Li
Han Ding
Shaohong Zhang
200
1
0
16 Jun 2023
A Neural Pairwise Ranking Model for Readability Assessment
A Neural Pairwise Ranking Model for Readability AssessmentFindings (Findings), 2022
Justin Lee
Sowmya Vajjala
142
37
0
14 Mar 2022
Using Conversational Artificial Intelligence to Support Children's
  Search in the Classroom
Using Conversational Artificial Intelligence to Support Children's Search in the Classroom
Garrett Allen
Jie Yang
M. S. Pera
U. Gadiraju
177
1
0
30 Nov 2021
Word embeddings for topic modeling: an application to the estimation of
  the economic policy uncertainty index
Word embeddings for topic modeling: an application to the estimation of the economic policy uncertainty indexExpert systems with applications (ESWA), 2021
Hairo U. Miranda Belmonte
Victor Muniz-Sánchez
F. Corona
106
13
0
29 Oct 2021
Concept Identification of Directly and Indirectly Related Mentions
  Referring to Groups of Persons
Concept Identification of Directly and Indirectly Related Mentions Referring to Groups of Persons
Anastasia Zhukova
Felix Hamborg
K. Donnay
Bela Gipp
115
2
0
02 Jul 2021
Trends, Limitations and Open Challenges in Automatic Readability
  Assessment Research
Trends, Limitations and Open Challenges in Automatic Readability Assessment ResearchInternational Conference on Language Resources and Evaluation (LREC), 2021
Sowmya Vajjala
182
59
0
03 May 2021
Tired of Topic Models? Clusters of Pretrained Word Embeddings Make for
  Fast and Good Topics too!
Tired of Topic Models? Clusters of Pretrained Word Embeddings Make for Fast and Good Topics too!Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020
Suzanna Sia
Ayush Dalmia
Sabrina J. Mielke
238
175
0
30 Apr 2020
Clustering without Over-Representation
Clustering without Over-RepresentationKnowledge Discovery and Data Mining (KDD), 2019
Sara Ahmadian
Alessandro Epasto
Ravi Kumar
Mohammad Mahdian
148
112
0
29 May 2019
Sequential Embedding Induced Text Clustering, a Non-parametric Bayesian
  Approach
Sequential Embedding Induced Text Clustering, a Non-parametric Bayesian Approach
Tiehang Duan
Qi Lou
S. Srihari
Xiaohui Xie
BDL
107
7
0
29 Nov 2018
1