Computational Methods for Information Processing from Natural Language Complaint Processes—A Systematic Review
Complaint processing is of great importance for companies because it allows them to understand customer satisfaction levels, which is crucial for business success. It allows them to show the real perceptions of users and thus visualize the problems, which are regularly processed from oral or written...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Computers |
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| Online Access: | https://www.mdpi.com/2073-431X/14/1/28 |
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| author | J. C. Blandón Andrade A. Castaño Toro A. Morales Ríos D. Orozco Ospina |
| author_facet | J. C. Blandón Andrade A. Castaño Toro A. Morales Ríos D. Orozco Ospina |
| author_sort | J. C. Blandón Andrade |
| collection | DOAJ |
| description | Complaint processing is of great importance for companies because it allows them to understand customer satisfaction levels, which is crucial for business success. It allows them to show the real perceptions of users and thus visualize the problems, which are regularly processed from oral or written natural language, derived from the provision of a service. In addition, the treatment of complaints is relevant because according to the laws of each country, companies have the obligation to respond to these complaints in a specified time. The specialized literature mentions that enterprises lost USD 75 billion due to poor customer service, highlighting that companies need to know and understand customer perceptions, especially emotions, and product reviews to gain insight and learn about customer feedback because of the importance of the voice of the customer for an organization. In general, it is evident that there is a need for research related to computational language processing to handle user requests. The authors show great interest in computational techniques for the processing of this information in natural language and how this could contribute to the improvement of processes within the productive sector. This work searches in indexed journals for information related to computational methods for processing relevant data from user complaints. It is proposed to apply a systematic literature review (SLR) method combining literature review guides by Kitchenham and the PRISMA statement. The systematic process allows the extraction of consistent information, and after applying it, 27 articles were obtained from which the analysis was conducted. The results show various proposals using linguistic, statistical, machine learning, and hybrid methods. We find that most authors combine Natural Language Processing (NLP) and Machine Learning (ML) to create hybrid methods. The methods extract relevant information from complaints of the customers in natural language in various domains, such as government, medical, banks, e-commerce, public services, agriculture, customer service, environmental, and tourism, among others. This work contributes as support for the creation of new systems that can give companies a significant competitive advantage due to their ability to reduce the response time of the complaints as established by law. |
| format | Article |
| id | doaj-art-3dee0ef16e9c4e33aeecb5954e767949 |
| institution | Kabale University |
| issn | 2073-431X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computers |
| spelling | doaj-art-3dee0ef16e9c4e33aeecb5954e7679492025-01-24T13:27:55ZengMDPI AGComputers2073-431X2025-01-011412810.3390/computers14010028Computational Methods for Information Processing from Natural Language Complaint Processes—A Systematic ReviewJ. C. Blandón Andrade0A. Castaño Toro1A. Morales Ríos2D. Orozco Ospina3Systems and Telecommunications Engineering Program, Catholic University of Pereira, Pereira 60001, ColombiaSystems and Telecommunications Engineering Program, Catholic University of Pereira, Pereira 60001, ColombiaSystems and Telecommunications Engineering Program, Catholic University of Pereira, Pereira 60001, ColombiaPereira Energy Company, Pereira 60003, ColombiaComplaint processing is of great importance for companies because it allows them to understand customer satisfaction levels, which is crucial for business success. It allows them to show the real perceptions of users and thus visualize the problems, which are regularly processed from oral or written natural language, derived from the provision of a service. In addition, the treatment of complaints is relevant because according to the laws of each country, companies have the obligation to respond to these complaints in a specified time. The specialized literature mentions that enterprises lost USD 75 billion due to poor customer service, highlighting that companies need to know and understand customer perceptions, especially emotions, and product reviews to gain insight and learn about customer feedback because of the importance of the voice of the customer for an organization. In general, it is evident that there is a need for research related to computational language processing to handle user requests. The authors show great interest in computational techniques for the processing of this information in natural language and how this could contribute to the improvement of processes within the productive sector. This work searches in indexed journals for information related to computational methods for processing relevant data from user complaints. It is proposed to apply a systematic literature review (SLR) method combining literature review guides by Kitchenham and the PRISMA statement. The systematic process allows the extraction of consistent information, and after applying it, 27 articles were obtained from which the analysis was conducted. The results show various proposals using linguistic, statistical, machine learning, and hybrid methods. We find that most authors combine Natural Language Processing (NLP) and Machine Learning (ML) to create hybrid methods. The methods extract relevant information from complaints of the customers in natural language in various domains, such as government, medical, banks, e-commerce, public services, agriculture, customer service, environmental, and tourism, among others. This work contributes as support for the creation of new systems that can give companies a significant competitive advantage due to their ability to reduce the response time of the complaints as established by law.https://www.mdpi.com/2073-431X/14/1/28complaint processcomputational methodsdeep learningmachine learningnatural language processingsystematic literature review |
| spellingShingle | J. C. Blandón Andrade A. Castaño Toro A. Morales Ríos D. Orozco Ospina Computational Methods for Information Processing from Natural Language Complaint Processes—A Systematic Review Computers complaint process computational methods deep learning machine learning natural language processing systematic literature review |
| title | Computational Methods for Information Processing from Natural Language Complaint Processes—A Systematic Review |
| title_full | Computational Methods for Information Processing from Natural Language Complaint Processes—A Systematic Review |
| title_fullStr | Computational Methods for Information Processing from Natural Language Complaint Processes—A Systematic Review |
| title_full_unstemmed | Computational Methods for Information Processing from Natural Language Complaint Processes—A Systematic Review |
| title_short | Computational Methods for Information Processing from Natural Language Complaint Processes—A Systematic Review |
| title_sort | computational methods for information processing from natural language complaint processes a systematic review |
| topic | complaint process computational methods deep learning machine learning natural language processing systematic literature review |
| url | https://www.mdpi.com/2073-431X/14/1/28 |
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