App Review Analysis Via Active Learning: Reducing Supervision Effort without Compromising Classification Accuracy-Reference-Cited by-同舟云学术

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App Review Analysis Via Active Learning: Reducing Supervision Effort without Compromising Classification Accuracy

Published:2018-08 Issue: Volume: Page:
ISSN:
Container-title:2018 IEEE 26th International Requirements Engineering Conference (RE)
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Author:

Dhinakaran Venkatesh T.,Pulle Raseshwari,Ajmeri Nirav,Murukannaiah Pradeep K.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8490808/8491107/08491133.pdf?arnumber=8491133

Cited by 45 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. Mining software insights: uncovering the frequently occurring issues in low-rating software applications;PeerJ Computer Science;2024-07-10

2. How to effectively mine app reviews concerning software ecosystem? A survey of review characteristics;Journal of Systems and Software;2024-07

3. Automatic Requirement Dependency Extraction Based on Integrated Active Learning Strategies;Machine Intelligence Research;2024-02-22

4. Factors Influencing Mobile App User Experience: An Analysis of Education App User Reviews;2024 4th International Conference on Advanced Research in Computing (ICARC);2024-02-21

5. Comparative Analysis of Negative Customer Review of Payment Apps: A Data Mining Approach;Lecture Notes in Networks and Systems;2024

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