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1. Alleviating Dimensional Collapse Problem in Deep Recommender Models by Designing Uniformity Layers NSTL国家科技图书文献中心

Yabin Zhang | Jiakai Tang ... - 《Database Systems for Advanced Applications,Part III》 - International Conference on Database Systems for Advanced Applications | International Workshop on Big Data Management and Service | International Workshop on Graph Data Management and Analysis | International Workshop on Big Data Quality Management | Workshop on Emerging Results inData Science and Engineering - 2025, - 148～163 - 共16页

摘要：Deep recommender models have shown remarkable | successes in real-world applications. Despite | effectiveness, it has been observed that as the number of | model layers goes larger, the learned embeddings may | become more and more similar (called the dimensional

关键词： Deep recommender models | Dimensional collapse

2. Variational Kernel Density Estimation Recommendation Algorithm for Users with Diverse Activity Levels NSTL国家科技图书文献中心

Wei Liu | Shangsong Liang ... - 《Database Systems for Advanced Applications,Part II》 - International Conference on Database Systems for Advanced Applications | International Workshop on Big Data Management and Service | International Workshop on Graph Data Management and Analysis | International Workshop on Big Data Quality Management | Workshop on Emerging Results inData Science and Engineering - 2025, - 3～18 - 共16页

摘要：Top-N recommendation is widely accepted as an | effective method in personalized service that well serves | users of different interests. However, as analyzed | from the SOTAs, their performance on the users with | diverse activity levels has significant distinction

关键词： Variational autoEncoder | Kernel density estimation | Implicit feedback | Personalized recommendation

3. Detecting Incoming Fake News in News Streams via Efficient Topic-Based Correlation NSTL国家科技图书文献中心

Xiaomei Wei | Yongcheng Zhang ... - 《Database Systems for Advanced Applications,Part II》 - International Conference on Database Systems for Advanced Applications | International Workshop on Big Data Management and Service | International Workshop on Graph Data Management and Analysis | International Workshop on Big Data Quality Management | Workshop on Emerging Results inData Science and Engineering - 2025, - 446～455 - 共10页

摘要：The news stream on social media has become the | primary source for instant insights into real-world | topics. However, the rapid spread of fake news poses a | significant challenge that needs to be strictly addressed | . Existing fake news detection methods analyze individual

关键词： Fake news detection | Incremental clustering | Domain adaptation network

4. Time-aware Dual-kernel Hawkes Process for Sequential Recommendation NSTL国家科技图书文献中心

Jingyang Liu | Nan Wang ... - 《Database Systems for Advanced Applications,Part II》 - International Conference on Database Systems for Advanced Applications | International Workshop on Big Data Management and Service | International Workshop on Graph Data Management and Analysis | International Workshop on Big Data Quality Management | Workshop on Emerging Results inData Science and Engineering - 2025, - 275～290 - 共16页

摘要：Sequence recommendation systems usually learn | users personalized preferences based on historical | behavior sequences of users. Previous methods often use | rich item interaction informations combined with | context to mine user sequential patterns. However, the

关键词： Hawkes process | Sequential recommendation | Self attention

5. RoNID: New Intent Discovery with Generated-Reliable Labels and Cluster-friendly Representations NSTL国家科技图书文献中心

Shun Zhang | Chaoran Yan ... - 《Database Systems for Advanced Applications,Part V》 - International Conference on Database Systems for Advanced Applications | International Workshop on Big Data Management and Service | International Workshop on Graph Data Management and Analysis | International Workshop on Big Data Quality Management | Workshop on Emerging Results inData Science and Engineering - 2025, - 104～119 - 共16页

摘要：New Intent Discovery (NID) strives to identify | known and reasonably deduce novel intent groups in the | open-world scenario. But current methods face issues | with inaccurate pseudo-labels and poor representation | learning, creating a negative feedback loop that degrades

关键词： New intent discovery | Reliable pseudo-labels generation | Cluster-friendly representation learning

6. A Prototypical Classifier with Boosting Augmented Redundancy Detector for Causal Analysis of Mental Health over Social Media NSTL国家科技图书文献中心

Yiping Liang | Linlin Wang ... - 《Database Systems for Advanced Applications,Part V》 - International Conference on Database Systems for Advanced Applications | International Workshop on Big Data Management and Service | International Workshop on Graph Data Management and Analysis | International Workshop on Big Data Quality Management | Workshop on Emerging Results inData Science and Engineering - 2025, - 155～172 - 共18页

摘要：Online social media are frequently used by | people as a way of expressing their thoughts and | feelings. Among the vast amounts of online posts, there | may be more concerning ones expressing potential | grievances and mental illnesses. Identifying these along

关键词： Causal analysis of mental health | Prompt learning

7. Boundary Point Detection Combining Gravity and Outlier Detection Methods NSTL国家科技图书文献中心

Vijdan Khalique | Hiroyuki Kitagawa ... - 《Database Systems for Advanced Applications》 - International Conference on Database Systems for Advanced Applications | International Workshop on Big Data Management and Service | International Workshop on Graph Data Management and Analysis | International Workshop on Big Data Quality Management | Workshop on Emerging Results inData Science and Engineering - 2025, - 147～162 - 共16页

摘要：Boundary point detection is the task of | identifying points occurring at the boundary of a dense | region in a dataset. It can reveal useful information | about the system generating the data. Several data | mining methods have been proposed to solve this problem

关键词： Boundary point detection | Cluster boundary | Data mining

8. Enhancing Link Prediction Based on Simple Path Graphs NSTL国家科技图书文献中心

Zhiren Li | Yuzheng Cai ... - 《Database Systems for Advanced Applications》 - International Conference on Database Systems for Advanced Applications | International Workshop on Big Data Management and Service | International Workshop on Graph Data Management and Analysis | International Workshop on Big Data Quality Management | Workshop on Emerging Results inData Science and Engineering - 2025, - 319～334 - 共16页

摘要：Link prediction is one of the prominent tasks | in the field of graph machine learning, aiming to | fill in missing edges in graph data or predict | potential connections between nodes in the graph. Early | link prediction methods primarily utilized

关键词： Graph neural network | Link prediction | Simple path graph

9. A Meta-learning Approach for Category-Aware Sequential Recommendation on POIs NSTL国家科技图书文献中心

Jia-Ling Koh | Po-Jen Wen ... - 《Database Systems for Advanced Applications》 - International Conference on Database Systems for Advanced Applications | International Workshop on Big Data Management and Service | International Workshop on Graph Data Management and Analysis | International Workshop on Big Data Quality Management | Workshop on Emerging Results inData Science and Engineering - 2025, - 163～177 - 共15页

摘要：The goal of sequential recommendation is to | gain valuable insights from previous interactions | between users and items to predict the next item that | the user maybe interest. In this research, an | enhancement of the Meta Transitional Learning (MetaTL

关键词： Sequential recommendation | Category-aware | Meta-learning

10. Construction of EMU Fault Knowledge Graph Based on Large Language Model NSTL国家科技图书文献中心

Ziwei Han | Hui Wang ... - 《Database Systems for Advanced Applications》 - International Conference on Database Systems for Advanced Applications | International Workshop on Big Data Management and Service | International Workshop on Graph Data Management and Analysis | International Workshop on Big Data Quality Management | Workshop on Emerging Results inData Science and Engineering - 2025, - 335～347 - 共13页

摘要：During the operation of the EMU, a large | number of fault data will be generated, which record | the fault overview, fault cause, treatment measures | and other related fault information. Construction of | knowledge graph of these data can provide knowledge for

摘要：Deep recommender models have shown remarkable | successes in real-world applications. Despite | effectiveness, it has been observed that as the number of | model layers goes larger, the learned embeddings may | become more and more similar (called the dimensional

关键词： Deep recommender models | Dimensional collapse

摘要：Top-N recommendation is widely accepted as an | effective method in personalized service that well serves | users of different interests. However, as analyzed | from the SOTAs, their performance on the users with | diverse activity levels has significant distinction

关键词： Variational autoEncoder | Kernel density estimation | Implicit feedback | Personalized recommendation

摘要：The news stream on social media has become the | primary source for instant insights into real-world | topics. However, the rapid spread of fake news poses a | significant challenge that needs to be strictly addressed | . Existing fake news detection methods analyze individual

关键词： Fake news detection | Incremental clustering | Domain adaptation network

摘要：Sequence recommendation systems usually learn | users personalized preferences based on historical | behavior sequences of users. Previous methods often use | rich item interaction informations combined with | context to mine user sequential patterns. However, the

关键词： Hawkes process | Sequential recommendation | Self attention

摘要：New Intent Discovery (NID) strives to identify | known and reasonably deduce novel intent groups in the | open-world scenario. But current methods face issues | with inaccurate pseudo-labels and poor representation | learning, creating a negative feedback loop that degrades

关键词： New intent discovery | Reliable pseudo-labels generation | Cluster-friendly representation learning

摘要：Online social media are frequently used by | people as a way of expressing their thoughts and | feelings. Among the vast amounts of online posts, there | may be more concerning ones expressing potential | grievances and mental illnesses. Identifying these along

关键词： Causal analysis of mental health | Prompt learning

摘要：Boundary point detection is the task of | identifying points occurring at the boundary of a dense | region in a dataset. It can reveal useful information | about the system generating the data. Several data | mining methods have been proposed to solve this problem

关键词： Boundary point detection | Cluster boundary | Data mining

摘要：Link prediction is one of the prominent tasks | in the field of graph machine learning, aiming to | fill in missing edges in graph data or predict | potential connections between nodes in the graph. Early | link prediction methods primarily utilized

关键词： Graph neural network | Link prediction | Simple path graph

摘要：The goal of sequential recommendation is to | gain valuable insights from previous interactions | between users and items to predict the next item that | the user maybe interest. In this research, an | enhancement of the Meta Transitional Learning (MetaTL

关键词： Sequential recommendation | Category-aware | Meta-learning

摘要：During the operation of the EMU, a large | number of fault data will be generated, which record | the fault overview, fault cause, treatment measures | and other related fault information. Construction of | knowledge graph of these data can provide knowledge for

关键词： Large language model | Knowledge graph | EMU fault | Ontology model

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