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- ArticleApril 2024
Summarizing Doctor’s Diagnoses and Suggestions from Medical Dialogues
AbstractNowadays, doctors can provide consultation services to patients by dialogues on the online medical platforms, and need to summarize their diagnoses and suggestions according to the regulations of the platform, which will play an important guiding ...
- research-articleApril 2024
Peer prediction for learning agents
NIPS '22: Proceedings of the 36th International Conference on Neural Information Processing SystemsNovember 2022, Article No.: 1256, Pages 17276–17286Peer prediction refers to a collection of mechanisms for eliciting information from human agents when direct verification of the obtained information is unavailable. They are designed to have a game-theoretic equilibrium where everyone reveals their ...
- research-articleDecember 2023
Pseudo dense counterfactual augmentation for aspect-based sentiment analysis
AbstractAspect-based sentiment analysis (ABSA) is a fine-grained text classification task, and the cutting-edge ABSA models have achieved outstanding performance. Unfortunately, the robustness of these ABSA models is neglected. ABSA models must face ...
- research-articleOctober 2023
Few-shot Multimodal Sentiment Analysis Based on Multimodal Probabilistic Fusion Prompts
MM '23: Proceedings of the 31st ACM International Conference on MultimediaOctober 2023, Pages 6045–6053https://doi.org/10.1145/3581783.3612181Multimodal sentiment analysis has gained significant attention due to the proliferation of multimodal content on social media. However, existing studies in this area rely heavily on large-scale supervised data, which is time-consuming and labor-intensive ...
- ArticleOctober 2023
Generating Better Responses from User Feedback via Reinforcement Learning and Commonsense Inference
Natural Language Processing and Chinese ComputingOct 2023, Pages 376–387https://doi.org/10.1007/978-3-031-44699-3_34AbstractDialogue generation task is one of the popular research topics in the field of natural language processing. However, how to improve the quality of model generated responses with the user feedback in the dialogue generation task is still one of the ...
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- research-articleOctober 2023
Graph neural network for recommendation in complex and quaternion spaces
World Wide Web (WWWJ), Volume 26, Issue 6Nov 2023, Pages 3945–3964https://doi.org/10.1007/s11280-023-01210-xAbstractWith the development of graph neural network, researchers begin to use bipartite graph to model user-item interactions for recommendation. It is worth noting that most of graph recommendation models represent users and items in the real-valued ...
- research-articleSeptember 2023
Distribution-based Learnable Filters with Side Information for Sequential Recommendation
RecSys '23: Proceedings of the 17th ACM Conference on Recommender SystemsSeptember 2023, Pages 78–88https://doi.org/10.1145/3604915.3608782Sequential Recommendation aims to predict the next item by mining out the dynamic preference from user previous interactions. However, most methods represent each item as a single fixed vector, which is incapable of capturing the uncertainty of item-...
- research-articleSeptember 2023
OERL: Enhanced Representation Learning via Open Knowledge Graphs
IEEE Transactions on Knowledge and Data Engineering (IEEECS_TKDE), Volume 35, Issue 9Sept. 2023, Pages 8880–8892https://doi.org/10.1109/TKDE.2022.3218850The sparseness and incompleteness of knowledge graphs (KGs) trigger considerable interest in enhancing the representation learning with external corpora. However, the difficulty of aligning entities and relations with external corpora leads to inferior ...
- research-articleAugust 2023
Prognostic fault prevention by segmented digital transformation of manufacturing process signals
Advanced Engineering Informatics (ADEI), Volume 57, Issue CAug 2023https://doi.org/10.1016/j.aei.2023.102125Highlights- A fault trend prediction algorithm is proposed to solve the post-mortem problem in fault diagnostics.
- An indicator is created to reflect the state change of the signal.
- A deep learning-like algorithm is proposed to predict and ...
Faults during operation of a system can occur at any time. Contemporary fault diagnosis systems focus on identifying the problem. However, when faults occur, the system has already incurred losses, either as rejects or machine damage. In this ...
- research-articleJuly 2023
Deep transition network with gating mechanism for multivariate time series forecasting
Applied Intelligence (KLU-APIN), Volume 53, Issue 20Pages 24346–24359https://doi.org/10.1007/s10489-023-04503-wAbstractAs an essential task in the machine learning community, multivariate time series forecasting has many real-world applications, such as PM2.5 forecasting, electricity price forecasting, and traffic flow forecasting. In multivariate time series data,...
- abstractJune 2023
Machine Explanations and Human Understanding
FAccT '23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and TransparencyJune 2023, Page 1https://doi.org/10.1145/3593013.3593970Explanations are hypothesized to improve human understanding of machine learning models and achieve a variety of desirable outcomes, ranging from model debugging to enhancing human decision making. However, empirical studies have found mixed and even ...
- ArticleApril 2023
Optimizing Empathetic Response by Generating and Integrating Emotion Feedback and Topic Discussion
Database Systems for Advanced ApplicationsApr 2023, Pages 623–638https://doi.org/10.1007/978-3-031-30675-4_46AbstractExpressing empathy is a trait in human daily conversation, in which people are willing to give responses containing appropriate emotions and topics on the basis of understanding the interlocutor’s situation. However, empathetic dialogue models ...
- ArticleFebruary 2023
KEP-Rec: A Knowledge Enhanced User-Item Relation Prediction Model for Personalized Recommendation
AbstractFor more accurate, diversified and interpretable personalized recommendation, the joint consideration of user-item interaction information and side information in knowledge graph has become a research hotspot. Traditional models based on ...
- research-articleFebruary 2023
Combinatorial causal bandits
AAAI'23/IAAI'23/EAAI'23: Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial IntelligenceFebruary 2023, Article No.: 848, Pages 7550–7558https://doi.org/10.1609/aaai.v37i6.25917In combinatorial causal bandits (CCB), the learning agent chooses at most K variables in each round to intervene, collects feedback from the observed variables, with the goal of minimizing expected regret on the target variable Y. We study under the ...
- ArticleFebruary 2023
Participatory Design and Early Deployment of DarumaTO-3 Social Robot
- Zhihao Shen,
- Nanaka Urano,
- Chih-Pu Chen,
- Shi Feng,
- Scean Mitchell,
- Masao Katagiri,
- Yegang Du,
- Franco Pariasca Trevejo,
- Tito P. Tomo,
- Alexander Schmitz,
- Ryan Browne,
- Toshimi Ogawa,
- Yasuyuki Taki,
- Gabriele Trovato
AbstractWith the problem of ageing population increasingly prominent, the burden of families, caregivers and medical workers to take care of older adults will be heavier. Social exclusion and cognitive dysfunctions make things worse, especially in times ...
- research-articleJanuary 2023
Variational autoencoder densified graph attention for fusing synonymous entities: Model and protocol
Knowledge-Based Systems (KNBS), Volume 259, Issue CJan 2023https://doi.org/10.1016/j.knosys.2022.110061AbstractThe prediction of missing links of open knowledge graphs (OpenKGs) poses unique challenges compared with well-studied curated knowledge graphs (CuratedKGs). Unlike CuratedKGs whose entities are fully disambiguated against a fixed ...
Highlights- Propose a new model to automatically mine synonymous features.
- Design a novel ...
- research-articleDecember 2022
Aspect-based sentiment analysis with attention-assisted graph and variational sentence representation
Knowledge-Based Systems (KNBS), Volume 258, Issue CDec 2022https://doi.org/10.1016/j.knosys.2022.109975AbstractAspect-based sentiment analysis (ABSA) is a fine-grained task that detects the sentiment polarities of particular aspect words in a sentence. With the rise of graph convolution networks (GCNs), current ABSA models mostly use graph-based methods. ...
Highlights- Study aspect-based sentiment analysis tasks using two representations.
- Correct the dependency tree with self-attention to learn semantic information.
- Fuse more information at graph-level.
- Design a Variational encoder–decoder to ...
- ArticleOctober 2022
Graph Collaborative Filtering for Recommendation in Complex and Quaternion Spaces
Web Information Systems Engineering – WISE 2022Oct 2022, Pages 579–594https://doi.org/10.1007/978-3-031-20891-1_41AbstractWith the development of graph neural network, researchers begin to use bipartite graph to model user-item interactions for recommendation. It is worth noting that most of graph recommendation models represent users and items in the real-valued ...
- ArticleApril 2022
Knowledge-Enhanced Interactive Matching Network for Multi-turn Response Selection in Medical Dialogue Systems
Database Systems for Advanced ApplicationsApr 2022, Pages 255–262https://doi.org/10.1007/978-3-031-00129-1_19AbstractRecently, the response selection for retrieval-based dialogue systems has gained enormous attention from both academic and industrial communities. Although the previous methods achieve promising results for intelligent customer service systems and ...