التفاصيل البيبلوغرافية
| العنوان: |
RE-Miner: Mining mobile user reviews with feature extraction and emotion classification |
| المؤلفون: |
Motger de la Encarnación, Joaquim, Tiessler Aguirre, Max, Oriol Hilari, Marc, Bertolín Rico, Irene |
| المساهمون: |
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació, Universitat Politècnica de Catalunya. inSSIDE - integrated Software, Services, Information and Data Engineering |
| بيانات النشر: |
CEUR-WS.org |
| سنة النشر: |
2024 |
| المجموعة: |
Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledge |
| مصطلحات موضوعية: |
Àrees temàtiques de la UPC::Informàtica::Enginyeria del software, Requirements engineering, Mobile apps -- Evaluation, Mobile app reviews, Feature extraction, Emotion classification, Natural language processing, Enginyeria de requisits, Aplicacions mòbils -- Avaluació |
| الوصف: |
In the context of app stores, user reviews are pivotal on supporting multiple requirements engineering tasks. Among these, feature extraction and emotion classification play a crucial role in requirements prioritization, feedback gathering and release planning. Empirical evaluation of these techniques is impeded by data collection complexities and a lack of reproducible methods and available tools. Furthermore, existing studies often focus on isolated tasks, hindering a comprehensive analysis of user perceptions. This paper introduces RE-Miner, a work-in-progress tool integrating multiple feature extraction and emotion classification innovative methods, enabling a detailed analysis of feature-oriented user feedback. RE-Miner comprises a web-based service for task integration and comparison, and a web application for persistent storage and analytical visualization of reviews. As a result, RE-Miner provides a platform for seamless integration, replication, and comparison of review mining techniques, fostering advancements in feature extraction and emotion classification understanding for requirements engineering. A demo of the tool is showcased here: https://youtu.be/PFNCbborPuU. ; With the support from the Secretariat for Universities and Research of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund. This paper has been funded by the Spanish Ministerio de Ciencia e Innovación under project / funding scheme PID2020-117191RB-I00 / AEI/10.13039/501100011033. ; Peer Reviewed ; Postprint (published version) |
| نوع الوثيقة: |
conference object |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| تدمد: |
1613-0073 |
| Relation: |
https://ceur-ws.org/Vol-3672/PT-paper3.pdf; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-117191RB-I00/ES/DESARROLLO, OPERATIVA Y GOBERNANZA DE DATOS PARA SISTEMAS SOFTWARE BASADOS EN APRENDIZAJE AUTOMATICO/; Motger, Q. [et al.]. RE-Miner: Mining mobile user reviews with feature extraction and emotion classification. A: International Working Conference on Requirements Engineering: Foundation for Software Quality. "Joint Proceedings of REFSQ-2024 Workshops, Doctoral Symposium, Posters & Tools Track, and Education and Training Track: co-located with the 30th International Conference on Requirements Engineering: Foundation for Software Quality (REFSQ 2024): Winterthur, Switzerland, April 8-11, 2024". CEUR-WS.org, 2024, ISSN 1613-0073.; http://hdl.handle.net/2117/410278 |
| الاتاحة: |
http://hdl.handle.net/2117/410278 |
| Rights: |
Attribution 4.0 International ; http://creativecommons.org/licenses/by/4.0/ ; Open Access |
| رقم الانضمام: |
edsbas.B6AD22DD |
| قاعدة البيانات: |
BASE |
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