A Neural Generative Model for Joint Learning Topics and Topic-Specific Word Embeddings | Citedby Results | Transactions of the Association for Computational Linguistics | MIT Press

Skip to Main Content

Skip Nav Destination

A Neural Generative Model for Joint Learning Topics and Topic-Specific Word Embeddings

Transactions of the Association for Computational Linguistics (2020) 8: 471–485.

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

Different Machine Learning Algorithms used for Secure Software Advance using Software Repositories

International Journal of Scientific Research in Computer Science, Engineering and Information Technology 300.

Neural Embedding Allocation: Distributed Representations of Topic Models

Kamrun Naher Keya
Yannis Papanikolaou
James R. Foulds

Computational Linguistics (2022) 48 (4): 1021.

A Generative Model for Topic Discovery and Polysemy Embeddings on Directed Attributed Networks

Bianfang Chai
Xinyu Ji
Jianglin Guo
Lixiao Ma
Yibo Zheng

Symmetry (2022) 14 (4): 703.

Adaptive and hybrid context-aware fine-grained word sense disambiguation in topic modeling based document representation

Wenbo Li
Einoshin Suzuki

Information Processing & Management (2021) 58 (4): 102592.

Unsupervised Aspect Extraction Algorithm for opinion mining using topic modeling

Azizkhan F Pathan
Chetana Prakash

Global Transitions Proceedings (2021) 2 (2): 492.