Related references
Note: Only part of the references are listed.
Article
Computer Science, Artificial Intelligence
Bin Liang et al.
Summary: This paper proposes a graph convolutional network model Sentic GCN based on SenticNet to enhance the affective dependencies of sentences for aspect-based sentiment analysis. By integrating emotional knowledge from SenticNet, the model effectively handles contextual affective information in sentences, improving the effectiveness of sentiment polarity detection towards specific aspects.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Mauro Dragoni et al.
Summary: This article presents an improved version of OntoSenticNet that integrates knowledge-based representations and reasoning techniques to enhance the expressiveness and information reasoning capabilities of sentiment analysis systems.
IEEE INTELLIGENT SYSTEMS
(2022)
Review
Computer Science, Artificial Intelligence
Yosephine Susanto et al.
Summary: Sentic computing is a multi-disciplinary approach to sentiment analysis that combines affective computing and commonsense computing to better recognize, interpret, and process emotions and opinions on the web. Over the past decade, various models, resources, algorithms, and applications have been developed within the field of sentic computing. Future directions involve discussing advancements and developments in these areas.
COGNITIVE COMPUTATION
(2022)
Article
Green & Sustainable Science & Technology
Huaguo Chen et al.
Summary: Urban waste accumulation has changed the landscape of cities through environmental pollution. The utilization of urban waste in concrete shows immense potential as an alternative, bringing about environmental, economic, and technological benefits.
JOURNAL OF CLEANER PRODUCTION
(2022)
Review
Chemistry, Physical
Huaguo Chen et al.
Summary: Aluminum windows are crucial components of building envelopes, but they can be degraded by various factors. This review explores the deterioration mechanisms of aluminum windows under different environmental conditions and discusses advanced inspection techniques. Moisture and chloride ions have the most detrimental effect on aluminum windows in the long run, while mechanical loads can cause sudden damage. Infrared thermography and ultrasonic phased array technology are identified as effective methods for assessing the health of aluminum windows.
Editorial Material
Computer Science, Theory & Methods
David Camacho et al.
Summary: The rapid growth of social media platforms and their associated applications has revolutionized the way billions of people interact on the Web, driving innovations in user-centered applications and efficient data processing techniques. Recent advances in data science and artificial intelligence have made these developments possible, as evidenced by the 12 selected papers in this special issue representing the latest advances in fields like pattern recognition, information fusion, knowledge discovery, and data visualization.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Construction & Building Technology
Huaguo Chen et al.
Summary: The paper introduces a convolution-based deep learning model to accurately assess the mechanical performance of Fiber-reinforced concrete (FRC) exposed to high temperatures. The feasibility and accuracy of the model were validated using experimental data, where it outperformed multiple machine learning baseline models. The proposed model can assist researchers and engineers in optimizing FRC design and estimating compressive strength for various engineering needs.
CONSTRUCTION AND BUILDING MATERIALS
(2021)
Article
Computer Science, Artificial Intelligence
Iti Chaturvedi et al.
Summary: Evolutionary optimization approach called Genetic Programming (GP) is used to optimize multiple tasks simultaneously. By utilizing selective imitation and inter-task covariance, the model can evolve individuals with different skills for different tasks. A modular approach is introduced to preserve sub-neural architectures during crossover across multiple tasks.
COGNITIVE COMPUTATION
(2021)
Article
Computer Science, Theory & Methods
Mohammad Ehsan Basiri et al.
Summary: ABCDM is an attention-based bidirectional CNN-RNN deep model that utilizes bidirectional LSTM and GRU to extract contextual information from both past and future, applying attention mechanism to emphasize different words for sentiment analysis polarity detection.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Kia Dashtipour et al.
Summary: Recent studies show that utilizing multimodal data can effectively gauge public perception, and a Persian multimodal dataset and sentiment analysis framework are provided as research resources. Experimental results demonstrate that integrating multimodal features can enhance sentiment analysis performance.
Proceedings Paper
Computer Science, Artificial Intelligence
Peiqin Lin et al.
Summary: This paper proposes a framework of Hierarchical Inter-Clause Interaction Network (HICIN) that applies inter-clause interaction on both word-level and clause-level features, improving the performance of emotion cause extraction task effectively.
2021 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)
(2021)
Article
Acoustics
Zifeng Cheng et al.
Summary: This study reframes emotion-cause pair extraction as a unified sequence labeling problem, allowing to extract emotion-cause pairs through one pass of sequence labeling. The proposed unified target-oriented sequence-to-sequence model comprehensively utilizes the information of target clause, global context, and former decoded label to perform end-to-end unified sequence labeling, demonstrating its effectiveness through experimental results.
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING
(2021)
Article
Acoustics
Chuang Fan et al.
Summary: The study introduces a multi-task sequence tagging framework for extracting emotions and associated causes simultaneously, by encoding distances into a tagging scheme to achieve explicit and interpretable information exchange for emotion-cause pair extraction.
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING
(2021)
Article
Computer Science, Artificial Intelligence
Hao Tang et al.
Article
Business
Agnieszka Zablocki et al.
JOURNAL OF INTERACTIVE MARKETING
(2019)
Article
Computer Science, Artificial Intelligence
Weiming Liang et al.
EXPERT SYSTEMS WITH APPLICATIONS
(2018)
Proceedings Paper
Computer Science, Theory & Methods
M. D. Devika et al.
FOURTH INTERNATIONAL CONFERENCE ON RECENT TRENDS IN COMPUTER SCIENCE & ENGINEERING (ICRTCSE 2016)
(2016)
