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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-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 ...
- 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
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 ...
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- 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-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 ...
- 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 ...
- ArticleApril 2022
Collaborative Filtering for Recommendation in Geometric Algebra
Database Systems for Advanced ApplicationsApr 2022, Pages 256–263https://doi.org/10.1007/978-3-031-00126-0_17AbstractAt present, recommender system plays an important role in many practical applications. Many recommendation models are based on representation learning, in which users and items are embedded into a low-dimensional vector space, and then historical ...
- ArticleFebruary 2022
I Know You Better: User Profile Aware Personalized Dialogue Generation
Advanced Data Mining and ApplicationsFeb 2022, Pages 192–205https://doi.org/10.1007/978-3-030-95408-6_15AbstractRecently, the response generation for dialogue systems has become a research hotspot both in the academic and business communities. Existing personalized response generation methods mainly stand on the chatbot’s perspective, and focus on improving ...
- research-articleDecember 2021
Multimodal Emotion Recognition with Factorized Bilinear Pooling and Adversarial Learning
CSAE '21: Proceedings of the 5th International Conference on Computer Science and Application EngineeringOctober 2021, Article No.: 89, Pages 1–6https://doi.org/10.1145/3487075.3487164With the fast development of social networks, the massive growth of the number of multimodal data such as images and texts allows people have higher demands for information processing from an emotional perspective. Emotion recognition requires a higher ...
- research-articleNovember 2021
SINN: A speaker influence aware neural network model for emotion detection in conversations
World Wide Web (WWWJ), Volume 24, Issue 6Nov 2021, Pages 2019–2048https://doi.org/10.1007/s11280-021-00954-8AbstractInferring the sentiment polarity or emotion category of subjective text is the fundamental task of sentiment analysis. Recently, emotion detection in conversations that considering context utterances has emerged as a very important and challenging ...
- research-articleOctober 2021
Adaptive Posterior Knowledge Selection for Improving Knowledge-Grounded Dialogue Generation
CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge ManagementOctober 2021, Pages 1989–1998https://doi.org/10.1145/3459637.3482314In open-domain dialogue systems, knowledge information such as unstructured persona profiles, text descriptions and structured knowledge graph can help incorporate abundant background facts for delivering more engaging and informative responses. Existing ...
- short-paperOctober 2021
Span-level Emotion Cause Analysis with Neural Sequence Tagging
CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge ManagementOctober 2021, Pages 3227–3231https://doi.org/10.1145/3459637.3482186This paper addresses the task of span-level emotion cause analysis (SECA). It is a finer-grained emotion cause analysis (ECA) task, which aims to identify the specific emotion cause span(s) behind certain emotions in text. In this paper, we formalize ...
- short-paperOctober 2021
Span-Level Emotion Cause Analysis by BERT-based Graph Attention Network
CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge ManagementOctober 2021, Pages 3221–3226https://doi.org/10.1145/3459637.3482185We study the task of span-level emotion cause analysis (SECA), which is focused on identifying the specific emotion cause span(s) triggering a certain emotion in the text. Compared to the popular clause-level emotion cause analysis (CECA), it is a finer-...
- research-articleSeptember 2021
Learning to improve persona consistency in conversation generation with information augmentation
Knowledge-Based Systems (KNBS), Volume 228, Issue CSep 2021https://doi.org/10.1016/j.knosys.2021.107246AbstractIn an open-domain conversation system, maintaining consistent persona is a key factor to earn trust from users and engage users in the conversation. Existing methods suffer from the issue that only sparse persona-relevant signals are ...
- research-articleSeptember 2021
Dual-view hypergraph neural networks for attributed graph learning
Knowledge-Based Systems (KNBS), Volume 227, Issue CSep 2021https://doi.org/10.1016/j.knosys.2021.107185AbstractGraph embedding analyzes network data by learning the vector representation of each vertex in the network, and has attracted widespread attention in recent years. In many real-world networks, considering the topology and attributes of ...
- ArticleAugust 2021
Multi-level Emotion Cause Analysis by Multi-head Attention Based Multi-task Learning
AbstractEmotion cause analysis (ECA) aims to identify the potential causes behind certain emotions in text. Lots of ECA models have been designed to extract the emotion cause at the clause level. However, in many scenarios, only extracting the cause ...