As the smart materials, ionic polymer-metal composites (IPMCs), have a layered structure consisting of a polymeric membrane based on perfluorinated alkene, which is sandwiched between two noble metal-based electrodes,...
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Wireless Sensor Network (WSN) is a contemporary topic of research that has proven to be an advantageous technology for a wide variety of applications, including those dealing with the environment, the military, and he...
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作者：
Venkata Lavanya, T.Sivaraman, K.
Department of Computer Science and Engineering Tamil Nadu Chennai India
Dept of Computer Science and Engineering Tamil Nadu Chennai600073 India
The paper aims to establish a robust machine learning approach for accurately categorizing the level of physical activity based on data collected from wearable sensors. Data from more than 10,000 participants was gath...
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Cloud computing provides scalable and adaptable infrastructure however is significantly susceptible to cyber-attacks. This work presents a hybrid methodology that integrates the GOA and GA for feature selection, along...
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Current cloud-based systems face the challenge of managing storage and eliminating redundant data associated with the exponentially growing multimedia content, where numerous semantically similar but nonidentical file...
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Aspect-based sentiment analysis (ABSA) also known as phrase level, is a specific level of sentiment analysis task which tries to find the polarity of various aspects of an entity. It identifies aspects with in the giv...
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ISBN:
(纸本)9789819971367
Aspect-based sentiment analysis (ABSA) also known as phrase level, is a specific level of sentiment analysis task which tries to find the polarity of various aspects of an entity. It identifies aspects with in the given opinion and predicts the polarity corresponding to each aspect with in the text. In this research work, we proposed an aspect-based sentiment analysis for hotel services in Afaan Oromo texts using deep learning approach. Implementing this technique for hotel industries will have many significances. Tracking users’ opinions on the services they provide will help the organization understand their value in a competitive environment and to understand their customer opinion about the services. As there is no publicly available dataset used for this task, we have prepared an aspect-based sentiment analysis dataset from scratch by manually collecting the opinions from hotel customers by distributing a questionnaire. We have collected 1155 datasets for this research work through manually distributed questionnaires. The proposed solution has four steps: manual data collection, preprocessing, aspect category classification, and sentiment polarity classification. The classification process compares five deep learning models, CNN, LSTM, GRU, BiLSTM, and CNN-BiLSTM. In aspect category classification, we have six categories of aspects: Nyaata (Food), Dhugaatii (Drink), Bakka (Location), Gatii (Price), Keessummeessu (Reception), and Ciisicha (Room). In sentiment polarity classification, the polarity of each aspects is classified into either Negative or Positive classes. The result shows that the BiLSTM performed better than all the other models in both aspect category classification and sentiment polarity classification tasks. The BiLSTM model achieved an accuracy of 93.4% and an F1 score of 93% in the aspect category classification tasks. In the polarity classification task, BiLSTM achieved an accuracy of 87% and an F1 score of 88.9%. BiLSTM has been selected as a
The new coronavirus SARS-CoV-2, which triggered the COVID-19 pandemic, has had an unparalleled effect on economies, cultures, and world health. In response to the critical need for strict COVID-19 screening systems in...
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This paper introduces a new approach to switch authentication within a network environment, addressing the challenges associated with multiple switch configurations. The proposed continuous authentication process is s...
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Fungal infections at the skin of puppies, including dermatophytosis, are commonplace and pose great health dangers to each the animals and their proprietors. Although these infections do no longer affect human skin im...
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