A framework of Urdu topic modeling using latent dirichlet allocation (LDA)-Reference-Cited by-同舟云学术

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A framework of Urdu topic modeling using latent dirichlet allocation (LDA)

Published:2018-01 Issue: Volume: Page:
ISSN:
Container-title:2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC)
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Author:

Shakeel Khadija,Tahir Ghulam Rasool,Tehseen Irsha,Ali Mubashir

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8293728/8301613/08301655.pdf?arnumber=8301655

Cited by 9 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. A Local Explainability Technique for Graph Neural Topic Models;Human-Centric Intelligent Systems;2024-01-12

2. Revolutionizing Urdu Sentiment Analysis: Harnessing the Power of XLM-R and GPT-2;IEEE Access;2024

3. End to End Urdu Abstractive Text Summarization With Dataset and Improvement in Evaluation Metric;IEEE Access;2024

4. Context-aware Urdu Information Retrieval System;ACM Transactions on Asian and Low-Resource Language Information Processing;2023-03-31

5. Discovering Coherent Topics from Urdu Text: A Comparative Study of Statistical Models, Clustering Techniques and Word Embedding;2023 6th International Conference on Information and Computer Technologies (ICICT);2023-03

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