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检索条件"机构=Laboratory of Knowledge Data Engineering"
1024 条 记 录,以下是11-20 订阅
排序:
Representation learning: serial-autoencoder for personalized recommendation
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Frontiers of Computer Science 2024年 第4期18卷 61-72页
作者: Yi ZHU Yishuai GENG Yun LI Jipeng QIANG Xindong WU School of Information Engineering Yangzhou UniversityYangzhou 225127China Key Laboratory of Knowledge Engineering with Big Data(Ministry of Education of the People’s Republic of China) Hefei University of TechnologyHefei 230009China School of Computer Science and Information Engineering Hefei University of TechnologyHefei 230009China
Nowadays,the personalized recommendation has become a research hotspot for addressing information *** this,generating effective recommendations from sparse data remains a ***,auxiliary information has been widely used... 详细信息
来源: 评论
OEE-CFC: A dataset for Open Event Extraction from Chinese Financial Commentary
OEE-CFC: A Dataset for Open Event Extraction from Chinese Fi...
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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024
作者: Wan, Qizhi Wan, Changxuan Hu, Rong Liu, Dexi Xu, Wenwu Xu, Kang Zou, Meihua Liu, Tao Yang, Jie Xiong, Zhenwei School of Computer and Artificial Intelligence Jiangxi University of Finance and Economics Jiangxi Key Laboratory of Data and Knowledge Engineering China
To meet application needs, event extraction has shifted from simple entities to unconventional entities serving as event arguments. However, current corpora with unconventional entities as event arguments are limited ... 详细信息
来源: 评论
Cutting Learned Index into Pieces: An In-depth Inquiry into Updatable Learned Indexes  39
Cutting Learned Index into Pieces: An In-depth Inquiry into ...
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39th IEEE International Conference on data engineering, ICDE 2023
作者: Ge, Jiake Shi, Boyu Chai, Yanfeng Luo, Yuanhui Guo, Yunda He, Yinxuan Chai, Yunpeng Moe Key Laboratory of Data Engineering and Knowledge Engineering China Renmin University of China School of Information China
Numerous high-performance updatable learned indexes have recently been designed to support the writing requirements in practical systems. Researchers have proposed various strategies to improve the availability of upd... 详细信息
来源: 评论
Self-Adaptive Imbalanced Domain Adaptation With Deep Sparse Autoencoder
IEEE Transactions on Artificial Intelligence
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IEEE Transactions on Artificial Intelligence 2023年 第5期4卷 1293-1304页
作者: Zhu, Yi Wu, Xindong Li, Yun Qiang, Jipeng Yuan, Yunhao Yangzhou University School of Information Engineering Yangzhou225012 China Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Ministry of Education of China Hefei230002 China
Domain adaptation aims to transfer knowledge between different domains to develop an effective hypothesis in the target domain with scarce labeled data, which is an effective method for remedying the problem of labele... 详细信息
来源: 评论
Representation learning via an integrated autoencoder for unsupervised domain adaptation
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Frontiers of Computer Science 2023年 第5期17卷 75-87页
作者: Yi ZHU Xindong WU Jipeng QIANG Yunhao YUAN Yun LI School of Information Engineering Yangzhou UniversityYangzhou 225127China Key Laboratory of Knowledge Engineering with Big Data(Ministry of Education of China) Hefei University of TechnologyHefei 230009China School of Computer Science and Information Engineering Hefei University of TechnologyHefei 230601China
The purpose of unsupervised domain adaptation is to use the knowledge of the source domain whose data distribution is different from that of the target domain for promoting the learning task in the target *** key bott... 详细信息
来源: 评论
Efficient protocols for heavy hitter identification with local differential privacy
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Frontiers of Computer Science 2022年 第5期16卷 193-203页
作者: Dan ZHAO Suyun ZHAO Hong CHEN Ruixuan LIU Cuiping LI Wenjuan LIANG Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education Renmin University of ChinaBeijing 100872China School of Information Renmin University of ChinaBeijing 100872China
Local differential privacy(LDP),which is a technique that employs unbiased statistical estimations instead of real data,is usually adopted in data collection,as it can protect every user’s privacy and prevent the lea... 详细信息
来源: 评论
High Dynamic Collaborative Team Query via Multi-Fuzzy-Constrained Graph Pattern Matching  9
High Dynamic Collaborative Team Query via Multi-Fuzzy-Constr...
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9th International Conference on Cloud Computing and Big data Analytics, ICCCBDA 2024
作者: Hu, Tao Zhang, Zan Bu, Chenyang Li, Lei Key Laboratory of Knowledge Engineering with Big Data The Ministry of Education of China School of Computer Science and Information Engineering Hefei University of Technology Hefei China
Graph pattern matching is a technique widely used in various fields such as protein structure analysis, social group querying, and expert localization. This technique involves finding matching subgraphs in large socia... 详细信息
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Improving Parameter Estimation and Defensive Ability of Latent Dirichlet Allocation Model Training Under Rényi Differential Privacy
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Journal of Computer Science & Technology 2022年 第6期37卷 1382-1397页
作者: Tao Huang Su-Yun Zhao Hong Chen Yi-Xuan Liu Key Laboratory of Data Engineering and Knowledge Engineering(Renmin University of China) Ministry of Education Beijing 100087China School of Information Renmin University of ChinaBeijing 100087China
Latent Dirichlet allocation(LDA)is a topic model widely used for discovering hidden semantics in massive text *** Gibbs sampling(CGS),as a widely-used algorithm for learning the parameters of LDA,has the risk of priva... 详细信息
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Hierarchical All-Pairs SimRank Calculation  28th
Hierarchical All-Pairs SimRank Calculation
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28th International Conference on database Systems for Advanced Applications, DASFAA 2023
作者: Zhang, Liangfu Li, Cuiping Zhang, Xue Chen, Hong Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education School of Information Renmin University of China Beijing China
All-pairs SimRank calculation is a classic SimRank problem. However, all-pairs algorithms suffer from efficiency issues and accuracy issues. In this paper, we convert the non-linear simrank calculation into a new simp... 详细信息
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SGSH: Stimulate Large Language Models with Skeleton Heuristics for knowledge Base Question Generation
SGSH: Stimulate Large Language Models with Skeleton Heuristi...
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2024 Findings of the Association for Computational Linguistics: NAACL 2024
作者: Guo, Shasha Liao, Lizi Zhang, Jing Wang, Yanling Li, Cuiping Chen, Hong School of Information Renmin University of China Beijing China Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education China Singapore Management University Singapore Zhongguancun Laboratory China
knowledge base question generation (KBQG) aims to generate natural language questions from a set of triplet facts extracted from KB. Existing methods have significantly boosted the performance of KBQG via pre-trained ... 详细信息
来源: 评论