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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

ISBN: (纸本)9783031306747

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 simple closed formulation of linear system. And we come up with a sequence of novel algorithms to efficiently solve the linear system with accuracy guarantees. To reduce the memory consumption and improve the computational efficiency, we build a hierarchical framework to calculate the all-pairs SimRank scores, which includes locally coarse calculation and globally refine calculation. We first solve the local linear systems generated from the subgraphs, then we refine the SimRank scores on the full graph from the residuals of the local structures. We also show that our algorithms outperform the state-of-the-art all-pairs SimRank computation algorithms on real graphs. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computational efficiency

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Intelligent Fast Cell Association Scheme Based on Deep Q-Learning in Ultra-Dense Cellular Networks

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China Communications 2021年第2期18卷 259-270页

作者： Jinhua Pan Lusheng Wang Hai Lin Zhiheng Zha Caihong Kai Key Laboratory of Knowledge Engineering with Big Data Ministry of Education.School of Computer Science and Information EngineeringHefei University of TechnologyHefei 230601China Anhui Province Key Laboratory of Industry Safety and Emergency Technology Hefei 230601China Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education.School of Cyber Science and EngineeringWuhan UniversityWuhan 430072China

To support dramatically increased traffic loads,communication networks become *** cell association(CA)schemes are timeconsuming,forcing researchers to seek fast *** paper proposes a deep Q-learning based scheme,whose main idea is to train a deep neural network(DNN)to calculate the Q values of all the state-action pairs and the cell holding the maximum Q value is *** the training stage,the intelligent agent continuously generates samples through the trial-anderror method to train the DNN until *** the application stage,state vectors of all the users are inputted to the trained DNN to quickly obtain a satisfied CA result of a scenario with the same BS locations and user *** demonstrate that the proposed scheme provides satisfied CA results in a computational time several orders of magnitudes shorter than traditional ***,performance metrics,such as capacity and fairness,can be guaranteed.

关键词： ultra-dense cellular networks(UDCN) cell association(CA) deep Q-learning proportional fairness Q-learning

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A new algorithm for fast mining frequent itemsets using N-lists

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Science China(Information Sciences) 2012年第9期55卷 2008-2030页

作者： DENG ZhiHong ,WANG ZhongHui & JIANG JiaJian key {1. of Machine Perception(ministry of education),School of Electronics engineering and Computer Science,Peking University,Beijing 1.0871.China 1. Key Laboratory of Machine Perception (Ministry of Education) School of Electronics Engineering and Computer Science Peking University Beijing 100871 China

Mining frequent itemsets has emerged as a fundamental problem in data mining and plays an essential role in many important data mining *** this paper,we propose a novel vertical data representation called N-list,which originates from an FP-tree-like coding prefix tree called PPC-tree that stores crucial information about frequent *** on the N-list data structure,we develop an efficient mining algorithm,PrePost,for mining all frequent *** of PrePost is achieved by the following three ***,N-list is compact since transactions with common prefixes share the same nodes of the ***,the counting of itemsets’ supports is transformed into the intersection of N-lists and the complexity of intersecting two N-lists can be reduced to O(m + n) by an efficient strategy,where m and n are the cardinalities of the two N-lists ***,PrePost can directly find frequent itemsets without generating candidate itemsets in some cases by making use of the single path property of *** have experimentally evaluated PrePost against four state-of-the-art algorithms for mining frequent itemsets on a variety of real and synthetic *** experimental results show that the PrePost algorithm is the fastest in most *** though the algorithm consumes more memory when the datasets are sparse,it is still the fastest one.

关键词： data mining frequent itemset mining data structure N-lists algorithm

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Multi-view Feature Learning for the Over-penalty in Adversarial Domain Adaptation

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data Intelligence 2024年第1期6卷 183-200页

作者： Yuhong Zhang Jianqing Wu Qi Zhang Xuegang Hu School of Computer and Information Engineering Hefei University of TechnologyHefei 230601China Key Laboratory of Knowledge Engineering with Big Data(Hefei University of Technology) The Ministry of Education of ChinaHefei 230009China

Domain adaptation aims to transfer knowledge from the labeled source domain to an unlabeled target domain that follows a similar but different ***,adversarial-based methods have achieved remarkable success due to the excellent performance of domain-invariant feature presentation ***,the adversarial methods learn the transferability at the expense of the discriminability in feature representation,leading to low generalization to the target *** this end,we propose a Multi-view Feature Learning method for the Over-penalty in Adversarial Domain ***,multi-view representation learning is proposed to enrich the discriminative information contained in domain-invariant feature representation,which will counter the over-penalty for discriminability in adversarial ***,the class distribution in the intra-domain is proposed to replace that in the inter-domain to capture more discriminative information in the learning of transferrable *** experiments show that our method can improve the discriminability while maintaining transferability and exceeds the most advanced methods in the domain adaptation benchmark {1.sets.

关键词： domain adaptation adversarial learning multi-view learning

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Improving performance by creating a native join-index for OLAP

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Frontiers of Computer Science 2011年第2期5卷 236-249页

作者： Yansong ZHANG Shan WANG Jiaheng LU National Survey Research Center at Renmin University of China Beijing 100872 China Key Laboratory of the Ministry of Education for Data Engineering and Knowledge Engineering Renmin University of China Beijing 100872 China School of Information Renmin University of China Beijing 100872 China

The performance of online analytical processing （OLAP） is critical for meeting the increasing requirements of massive volume analytical applications. Typical techniques, such as in-memory processing, column-storage, and join indexes focus on high perfor- mance storage media, efficient storage models, and reduced query processing. While they effectively perform OLAP applications, there is a vital limitation： main- memory database based OLAP （MMOLAP） cannot provide high performance for a large size data set. In this paper, we propose a novel memory dimension table model, in which the primary keys of the dimension table can be directly mapped to dimensional tuple addresses. To achieve higher performance of dimensional tuple access, we optimize our storage model for dimension tables based on OLAP query workload features. We present directly dimensional tuple accessing （DDTA） based join （DDTA- JOIN）, a technique to optimize query processing on the memory dimension table by direct dimensional tuple access. We also contribute by proposing an optimization of the predicate tree to shorten predicate operation length by pruning useless predicate processing. Our experimental results show that the DDTA-JOIN algorithm is superior to both simulated row-store main memory query processing and the open-source column-store main memory database MonetDB, thanks to the reduced join cost and simple yet efficient query processing.

关键词： directly dimensional tuple accessing (DDTA) – DDTA JOIN – native join index – predicate tree

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Fractal model for simulation of frost formation and growth

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Science China(Technological Sciences) 2010年第3期53卷 807-812页

作者： LIU YaoMin,LIU ZhongLiang,HUANG LingYan&SUN JunFang education {1. key laboratory of Enhanced Heat Transfer and Energy Conservation,College of Environmental and Energy engineering,Beijing University of Technology,Beijing 1.01.4,China 1. Education Ministry Key Laboratory of Enhanced Heat Transfer and Energy Conservation College of Environmental and Energy Engineering Beijing University of Technology Beijing 100124 China

A planar fractal model for simulation of frost formation and growth was proposed based on diffusion limited aggregation(DLA)model and the computational simulation was carried out in this *** changing the times of program running circulation and the ratio of random particles generated,the simulation figures were gained under different conditions.A microscope is used to observe the shape and structure of frost layer and a digital camera with high resolution is used to record the pattern of frost layer at different *** comparing the simulation figures with the experimental images,we find that the simulation results agree well with the experimental images in shape and the fractal dimension of simulation figures is nearly equal to that of experimental *** results indicate that it is reasonable to represent frost layer growth time with the program circulation times and to simulate the frost layer density variation during its growth process by reducing the random particle generation *** feasibility of using the suggested model to simulate the process of frost formation and growth was *** insufficiencies and its causes of this fractal model are also discussed.

关键词： fractal frost formation and growth DLA simulation

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Capability description and discovery of Internetware entity

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Science China(Information Sciences) 2010年第4期53卷 685-703页

作者： WANG PuWei1., JIN Zhi2,3* & LIU HongYan4 1.0} {1. of data engineering and knowledge engineering of the ministry of education, Renmin University of China, Beijing 1.0872, China 2key {1. of High Confidence Software Technologies of the ministry of education, Peking University, Beijing 1.0871. China 3Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing 1.01.0, China 4Department of Management Science and engineering, Tsinghua University, Beijing 1.0084, China 1. Key Laboratory of Data Engineering and Knowledge Engineering of the Ministry of Education Renmin University of China Beijing 100872 China2. Key Laboratory of High Confidence Software Technologies of the Ministry of Education Peking University Beijing 100871 China3. Academy of Mathematics and System Sciences Chinese Academy of Sciences Beijing 100190 China4. Department of Management Science and Engineering Tsinghua University Beijing 100084 China

Internetware can be formed through aggregation of Internetware entities bottom-up to satisfy the user's requirements. In the process, capability description of Internetware entity plays an important role. This paper proposes a capability description of Internetware entity based on environment ontology. The environment ontology includes environment entities and possible interactions with the environment entities in a particular domain. Tree-like hierarchical state machines are also included in the ontology to describe domain life-cycle of the environment entities. On the basis of the ideas, the capability of Internetware entity is embodied by interacting with environment entities and the changes of the environment entities during the interactions. Finally, this paper describes the matchmaking between capability descriptions of Internetware entities to support the discovery of Internetware entity. An example of online education course is given to illustrate the ideas.

关键词： Internetware capability description domain environment ontology tree-like hierarchical state machine

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Effect of the cooling rate on plastic deformability of a Zr-based bulk metallic glass

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Science China(Physics,Mechanics & Astronomy) 2010年第3期53卷 415-418页

作者： ZHANG Jing, PANG ShuJie & ZHANG Tao key {1. of Aerospace Materials and Performance (ministry of education), Department of Materials Science and engineering, Beijing University of Aeronautics and Astronautics, Beijing 1.01.1. China 1. Key Laboratory of Aerospace Materials and Performance (Ministry of Education) Department of Materials Science and Engineering Beijing University of Aeronautics and Astronautics Beijing 100191 China

The present work found the plastic deformability of Zr65Cu1..5Ni1.Al7.5 BMG dependent on the cooling rate during the formation from the molten state alloy. The deformation behavior in the compression test of φ 2 mm Zr65Cu1..5Ni1.Al7.5 BMGs as-cast or lathed from different sizes as-cast samples was characterized, and they exhibited different plastic strains. The compressive plastic strain increases with the decreasing diameter of the as-cast specimens, i.e. with increasing the cooling rate. It is suggested that free volume content in the BMGs, which is related to the cooling rate during the rapid solidification, could play an important role in the deformation process of the BMGs.

关键词： cooling rate shear band serration bulk metallic glass

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Diversifying Question Generation over knowledge Base via External Natural Questions 30

Diversifying Question Generation over Knowledge Base via Ext...

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Joint 30th International Conference on Computational Linguistics and 1.th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Guo, Shasha Zhang, Jing Ke, Xirui 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

ISBN: (纸本)9782493814104

Previous methods on knowledge base question generation (KBQG) primarily focus on refining the quality of a single generated question. However, considering the remarkable paraphrasing ability of humans, we believe that diverse texts can express identical semantics through varied expressions. The above insights make diversifying question generation an intriguing task, where the first challenge is evaluation metrics for diversity. Current metrics inadequately assess the aforementioned diversity. They calculate the ratio of unique n-grams in the generated question, which tends to measure duplication rather than true diversity. Accordingly, we devise a new diversity evaluation metric, which measures the diversity among top-k generated questions for each instance while ensuring their relevance to the ground truth. Clearly, the second challenge is how to enhance diversifying question generation. To address this challenge, we introduce a dual model framework interwoven by two selection strategies to generate diverse questions leveraging external natural questions. The main idea of our dual framework is to extract more diverse expressions and integrate them into the generation model to enhance diversifying question generation. Extensive experiments on widely used benchmarks for KBQG show that our approach can outperform pre-trained language model baselines and text-davinci-003 in diversity while achieving comparable performance with ChatGPT. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Semantics

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DSM: Question Generation over knowledge Base via Modeling Diverse Subgraphs with Meta-learner

DSM: Question Generation over Knowledge Base via Modeling Di...

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2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022

作者： Guo, Shasha Zhang, Jing Wang, Yanling Zhang, Qianyi 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

Existing methods on knowledge base question generation (KBQG) learn a one-size-fits-all model by training together all subgraphs without distinguishing the diverse semantics of subgraphs. In this work, we show that making use of the past experience on semantically similar subgraphs can reduce the learning difficulty and promote the performance of KBQG models. To achieve this, we propose a novel approach to model diverse subgraphs with meta-learner (DSM). Specifically, we devise a graph contrastive learning-based retriever to identify semantically similar subgraphs, so that we can construct the semantics-aware learning tasks for the meta-learner to learn semantics-specific and semantics-agnostic knowledge on and across these tasks. Extensive experiments on two widely-adopted benchmarks for KBQG show that DSM derives new state-of-the-art performance and benefits the question answering tasks as a means of data augmentation. Codes and datasets are available online. © 2022 Association for Computational Linguistics.

关键词： Semantics

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