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Task and language in Spanish–English narratives (Wofford et al., 2022) ...
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Task and language in Spanish–English narratives (Wofford et al., 2022) ...
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Measuring and Comparing Social Bias in Static and Contextual Word Embeddings
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In: Dissertations (2022)
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A Corpus-Based Sentence Classifier for Entity–Relationship Modelling
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In: Electronics; Volume 11; Issue 6; Pages: 889 (2022)
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A Quantum Language-Inspired Tree Structural Text Representation for Semantic Analysis
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In: Mathematics; Volume 10; Issue 6; Pages: 914 (2022)
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An Unsupervised Approach to Structuring and Analyzing Repetitive Semantic Structures in Free Text of Electronic Medical Records
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In: Journal of Personalized Medicine; Volume 12; Issue 1; Pages: 25 (2022)
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Text Mining from Free Unstructured Text: An Experiment of Time Series Retrieval for Volcano Monitoring
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In: Applied Sciences; Volume 12; Issue 7; Pages: 3503 (2022)
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Detection of Chinese Deceptive Reviews Based on Pre-Trained Language Model
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In: Applied Sciences; Volume 12; Issue 7; Pages: 3338 (2022)
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Automated Customer Complaint Processing for Water Utilities Based on Natural Language Processing—Case Study of a Dutch Water Utility
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In: Water; Volume 14; Issue 4; Pages: 674 (2022)
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Abstract:
Most water utilities have to handle a substantial number of customer complaints every year. Traditionally, complaints are handled by skilled staff who know how to identify primary issues, classify complaints, find solutions, and communicate with customers. The effort associated with complaint processing is often great, depending on the number of customers served by a water utility. However, the rise of natural language processing (NLP), enabled by deep learning, and especially the use of deep recurrent and convolutional neural networks, has created new opportunities for comprehending and interpreting text complaints. As such, we aim to investigate the value of the use of NLP for processing customer complaints. Through a case study about the Water Utility Groningen in the Netherlands, we demonstrate that NLP can parse language structures and extract intents and sentiments from customer complaints. As a result, this study represents a critical and fundamental step toward fully automating consumer complaint processing for water utilities.
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Keyword:
artificial intelligence; customer complaint processing; natural language processing; water sector
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URL: https://doi.org/10.3390/w14040674
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52 |
MLLP-VRAIN Spanish ASR Systems for the Albayzín-RTVE 2020 Speech-to-Text Challenge: Extension
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In: Applied Sciences; Volume 12; Issue 2; Pages: 804 (2022)
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Transformer-Based Abstractive Summarization for Reddit and Twitter: Single Posts vs. Comment Pools in Three Languages
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In: Future Internet; Volume 14; Issue 3; Pages: 69 (2022)
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Using Conceptual Recurrence and Consistency Metrics for Topic Segmentation in Debate
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In: Applied Sciences; Volume 12; Issue 6; Pages: 2952 (2022)
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Connecting Text Classification with Image Classification: A New Preprocessing Method for Implicit Sentiment Text Classification
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In: Sensors; Volume 22; Issue 5; Pages: 1899 (2022)
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Predicting Institution Outcomes for Inter Partes Review (IPR) Proceedings at the United States Patent Trial & Appeal Board by Deep Learning of Patent Owner Preliminary Response Briefs
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In: Applied Sciences; Volume 12; Issue 7; Pages: 3656 (2022)
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Analysis of the Effects of Lockdown on Staff and Students at Universities in Spain and Colombia Using Natural Language Processing Techniques
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In: International Journal of Environmental Research and Public Health; Volume 19; Issue 9; Pages: 5705 (2022)
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FedQAS: Privacy-Aware Machine Reading Comprehension with Federated Learning
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In: Applied Sciences; Volume 12; Issue 6; Pages: 3130 (2022)
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A Dynamic Attention and Multi-Strategy-Matching Neural Network Based on Bert for Chinese Rice-Related Answer Selection
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In: Agriculture; Volume 12; Issue 2; Pages: 176 (2022)
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Correcting Diacritics and Typos with a ByT5 Transformer Model
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In: Applied Sciences; Volume 12; Issue 5; Pages: 2636 (2022)
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