Showing results 13 to 32 of 57
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| Issue Date | Title | Author(s) |
 | 2021 | Emotion recognition on edge devices: training and deployment | Pandelea, Vlad; Ragusa, Edoardo; Apicella, Tommaso; Gastaldo, Paolo; Cambria, Erik |
| | 2020 | End-to-end latent-variable task-oriented dialogue system with exact log-likelihood optimization | Xu, H.; Peng, Haiyun; Xie, H.; Cambria, Erik; Zhou, L.; Zheng, W. |
| 2014 | Enhancing business intelligence by means of suggestive reviews | Qazi, Atika; Raj, Ram Gopal; Tahir, Muhammad; Cambria, Erik; Syed, Karim Bux Shah |
| | 2017 | Ensemble application of ELM and GPU for real-time multimodal sentiment analysis | Tran, Ha-Nguyen; Cambria, Erik |
| 2022 | Ensemble hybrid learning methods for automated depression detection | Ansari, Luna; Ji, Shaoxiong; Chen, Qian; Cambria, Erik |
| | 2020 | Extracting time expressions and named entities with constituent-based tagging schemes | Zhong, Xiaoshi; Cambria, Erik; Hussain Amir |
| | 2019 | Fuzzy commonsense reasoning for multimodal sentiment analysis | Chaturvedi, Iti; Satapathy, Ranjan; Cavallari, Sandro; Cambria, Erik |
| | 2022 | Gender-based multi-aspect sentiment detection using multilabel learning | Kumar, J. Ashok; Trueman, Tina Esther; Cambria, Erik |
| | 2018 | A Generative Model for category text generation | Li, Yang; Pan, Quan; Wang, Suhang; Yang, Tao; Cambria, Erik |
| | 2019 | Growing semantic vines for robust asset allocation | Xing, Frank Z.; Cambria, Erik; Welsch, Roy E. |
| | 2020 | How intense are you? Predicting intensities of emotions and sentiments using stacked ensemble [application notes] | Akhtar, M. S.; Ekbal, A.; Cambria, Erik |
| | 2019 | Inconsistencies on TripAdvisor reviews : a unified index between users and Sentiment Analysis Methods | Valdivia, Ana; Hrabova, Emiliya; Chaturvedi, Iti; Luzón, M. Victoria; Troiano, Luigi; Cambria, Erik; Herrera, Francisco |
| | 2018 | Intelligent asset allocation via market sentiment views | Xing, Frank Z.; Cambria, Erik; Welsch, Roy E. |
| | 2019 | Learning binary codes with neural collaborative filtering for efficient recommendation systems | Li, Yang; Wang, Suhang; Pan, Quan; Peng, Haiyun; Yang, Tao; Cambria, Erik |
| | 2018 | Learning multi-grained aspect target sequence for Chinese sentiment analysis | Peng, Haiyun; Ma, Yukun; Li, Yang; Cambria, Erik |
| | 2019 | Learning with similarity functions : a tensor-based framework | Ragusa, Edoardo; Gastaldo, Paolo; Zunino, Rodolfo; Cambria, Erik |
| | 2022 | Meta-based self-training and re-weighting for aspect-based sentiment analysis | He, Kai; Mao, Rui; Gong, Tieliang; Li, Chen; Cambria, Erik |
| | 2022 | MetaPro: a computational metaphor processing model for text pre-processing | Mao, Rui; Li, Xiao; Ge, Mengshi; Cambria, Erik |
| | 2019 | Modelling customer satisfaction from online reviews using ensemble neural network and effect-based Kano model | Bi, Jian-Wu; Liu, Yang; Fan, Zhi-Ping; Cambria, Erik |
| | 2022 | Mood of the Planet: challenging visions of big data in the arts | Sorensen, Vibeke; Lansing, J. Stephen; Thummanapalli, Nagaraju; Cambria, Erik |
