Next Article in Journal
Anomaly Detection of IoT Cyberattacks in Smart Cities Using Federated Learning and Split Learning
Next Article in Special Issue
From Traditional Recommender Systems to GPT-Based Chatbots: A Survey of Recent Developments and Future Directions
Previous Article in Journal
A Novel Algorithm for Multi-Criteria Ontology Merging through Iterative Update of RDF Graph
Previous Article in Special Issue
Knowledge-Based and Generative-AI-Driven Pedagogical Conversational Agents: A Comparative Study of Grice’s Cooperative Principles and Trust
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
BDCC
Volume 8
Issue 3
10.3390/bdcc8030020
BDCC-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

A Machine Learning-Based Pipeline for the Extraction of Insights from Customer Reviews

by
Róbert Lakatos
1,2,*,
Gergő Bogacsovics
1,2,†,
Balázs Harangi
1,†,
István Lakatos
1,2,†,
Attila Tiba
1,†,
János Tóth
1,†,
Marianna Szabó
2,3,† and
András Hajdu
1,†
1
Department of Data Science and Visualization, Faculty of Informatics, University of Debrecen, H-4032 Debrecen, Hungary
2
Doctoral School of Informatics, University of Debrecen, H-4032 Debrecen, Hungary
3
Department of Applied Mathematics and Probability Theory, Faculty of Informatics, University of Debrecen, H-4032 Debrecen, Hungary
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Big Data Cogn. Comput. 2024, 8(3), 20; https://doi.org/10.3390/bdcc8030020
Submission received: 22 January 2024 / Revised: 15 February 2024 / Accepted: 19 February 2024 / Published: 22 February 2024
(This article belongs to the Special Issue Artificial Intelligence and Natural Language Processing)
Browse Figures
Versions Notes

Abstract

The efficiency of natural language processing has improved dramatically with the advent of machine learning models, particularly neural network-based solutions. However, some tasks are still challenging, especially when considering specific domains. This paper presents a model that can extract insights from customer reviews using machine learning methods integrated into a pipeline. For topic modeling, our composite model uses transformer-based neural networks designed for natural language processing, vector-embedding-based keyword extraction, and clustering. The elements of our model have been integrated and tailored to better meet the requirements of efficient information extraction and topic modeling of the extracted information for opinion mining. Our approach was validated and compared with other state-of-the-art methods using publicly available benchmark datasets. The results show that our system performs better than existing topic modeling and keyword extraction methods in this task.
Keywords: machine and deep learning; topic modeling; keyphrase extracting; natural language processing machine and deep learning; topic modeling; keyphrase extracting; natural language processing

Share and Cite

MDPI and ACS Style

Lakatos, R.; Bogacsovics, G.; Harangi, B.; Lakatos, I.; Tiba, A.; Tóth, J.; Szabó, M.; Hajdu, A. A Machine Learning-Based Pipeline for the Extraction of Insights from Customer Reviews. Big Data Cogn. Comput. 2024, 8, 20. https://doi.org/10.3390/bdcc8030020

AMA Style

Lakatos R, Bogacsovics G, Harangi B, Lakatos I, Tiba A, Tóth J, Szabó M, Hajdu A. A Machine Learning-Based Pipeline for the Extraction of Insights from Customer Reviews. Big Data and Cognitive Computing. 2024; 8(3):20. https://doi.org/10.3390/bdcc8030020

Chicago/Turabian Style

Lakatos, Róbert, Gergő Bogacsovics, Balázs Harangi, István Lakatos, Attila Tiba, János Tóth, Marianna Szabó, and András Hajdu. 2024. "A Machine Learning-Based Pipeline for the Extraction of Insights from Customer Reviews" Big Data and Cognitive Computing 8, no. 3: 20. https://doi.org/10.3390/bdcc8030020

APA Style

Lakatos, R., Bogacsovics, G., Harangi, B., Lakatos, I., Tiba, A., Tóth, J., Szabó, M., & Hajdu, A. (2024). A Machine Learning-Based Pipeline for the Extraction of Insights from Customer Reviews. Big Data and Cognitive Computing, 8(3), 20. https://doi.org/10.3390/bdcc8030020

Article Metrics

Back to TopTop