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6th International Conference on Image and Graphics Processing, ICIGP 2023

作者： Xu, Yueyuan Hu, Zhenzhen Zhou, Yuanen Hao, Shijie Hong, Richang Key Laboratory of Knowledge Engineering with Big Data School of Computer and Information Hefei University of Technology China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China

ISBN: (纸本)9781450398572

Current state-of-the-art image captioning models generate captions in a single language, requiring a combination of multiple language specific models to build a multilingual image captioning system. However, as the number of supported languages increases, it leads to the parameters of the multilingual image captioning system grow linearly. To tackle this issue, we propose a single Compact Interactive TransformEr (CITE) model, which can describe an image in multiple languages simultaneously, making the captioning system more compact. Specifically, based on the standard Transformer model, we share the encoder and decoder backbone parameters and replace the self-attention sub-layer in the decoder with the interactive attention sub-layer. In addition, we extend the traditional monolingual reinforcement learning mechanism to a multilingual version to promote better description generation. Due to the wide use of Chinese and English, we evaluate the performance of our CITE model by simultaneously generating English and Chinese captions. We expand the image captions of the whole MSCOCO dataset and release a COCO-EN-CN dataset. Extensive experiments on the COCO-EN-CN dataset show that our single CITE model with more parameter-efficient can maintain the competitive performance or even better than the monolingual captioning models. © 2023 ACM.

关键词： Reinforcement learning

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The Second-order h-type Indicators for Identifying Top Units

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data and Information Management 2018年第1期2卷 49-56页

作者： Ye, Fred Y. Bornmann, Lutz School of Information Management Nanjing University 210023 Nanjing China Jiangsu Key Laboratory of Data Engineering and Knowledge Service 210023 Nanjing China Administrative Headquarters of the Max Planck Society Division for Science and Innovation Studies Hofgartenstr. 8 D-80539 Munich Germany

The second-order h-type indicators are suggested to identify top units in scientometrics. Basically, the re-ranking of h-type series leads to the second-order h-type indicator. The second-order h-type indicators provide an interesting and natural method to identify top units, yielding fixed h-top. Differentiating from the series of artificially defined highly cited percentile classes, the h-top contributes a natural definite top in the series of highly cited classes. When studying theoretically, the second-order h-index concerns 3% of the h-top whereas the first-order h-index refers to 10% of the h-core. The ratio of the first- and second-order h-index, hT/h, is 30%. When studying empirically, the ratio of the first- and second-order h-index, hT/h, is © 2018 © 2018 Fred Y. Ye, Lutz Bornmann, published by Sciendo

关键词： Indexing (of information)

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Security Analysis Model, System Architecture and Relational Model of Enterprise Cloud Services

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International Journal of Automation and computing 2016年第6期13卷 574-584页

作者： Dang-Dang Niu Lei Liu Xin Zhang Shuai Lu Zhuang Li College of Computer Science and Technology Jilin University Changchun 130012 China Data Center Consolidation (Beijing) Industrial and Commercial Bank of China Beijing 100096 China College of Mathematics Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Changchun 130012 China

Cloud computing is one of the fastest growing and popular computer technologies, and there are more and more enterprise services based on the cloud computing. In order to save costs, more and more enterprises and their employees have hired the enterprise cloud services, and put much important information in the cloud gradually. Cloud service systems have become the main targets of malicious attacks. However, the cloud computing technologies are still not perfect, and the management and maintenance of enterprise cloud services are more complex compared to traditional network services of cloud computing. So, enterprise cloud services are more likely to encounter some security problems, and the influenced scale of these security problems is broad. But there are few researches on the security of enterprise cloud services. In this paper, we analyze the software as a service（Saa S） enterprise cloud services and introduce the research status of security problems in cloud computing environment. Combining with the analysis of the characteristics and application architecture of Saa S enterprise cloud services, we propose the security problems analysis model, the analysis system architecture and the relational model. Our researches can support further research of the automatic generation of solutions and guide the deployment of security policies of Saa S enterprise cloud services.

关键词： cloud deployment perfect maintenance likely users bases encounter relational costs

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FOSS: A Self-Learned Doctor for Query Optimizer 40

FOSS: A Self-Learned Doctor for Query Optimizer

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40th IEEE International Conference on data engineering, ICDE 2024

作者： Zhong, Kai Sun, Luming Ji, Tao Li, Cuiping Chen, Hong Renmin University of China China Key Laboratory of Data Engineering and Knowledge Engineering MOE China Shanghai Yunxi Technology Co. Ltd. China Engineering Research Center of Database and Business Intelligence MOE China

ISBN: (纸本)9798350317152

Various works have utilized deep learning to address the query optimization problem in database system. They either learn to construct plans from scratch in a bottom-up manner or steer the plan generation behavior of traditional optimizer using hints. While these methods have achieved some success, they face challenges in either low training efficiency or limited plan search space. To address these challenges, we introduce FOSS, a novel framework for query optimization based on deep reinforcement learning. FOSS initiates optimization from the original plan generated by a traditional optimizer and incrementally refines suboptimal nodes of the plan through a sequence of actions. Additionally, we devise an asymmetric advantage model to evaluate the advantage between two plans. We integrate it with a traditional optimizer to form a simulated environment. Leveraging this simulated environment, FOSS can bootstrap itself to rapidly generate a large amount of high-quality simulated experiences. FOSS then learns from these experiences to improve its optimization capability. We evaluate the performance of FOSS on Join Order Benchmark, TPC-DS, and Stack Overflow. The experimental results demonstrate that FOSS outperforms the state-of-the-art methods in terms of latency performance. Compared to PostgreSQL, FOSS achieves speedup ranging from 1.15x to 8.33x in total latency across different benchmarks. © 2024 IEEE.

关键词： Reinforcement learning

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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 1key laboratory of data engineering and knowledge engineering of the Ministry of Education, Renmin University of China, Beijing 100872, China 2key laboratory of High Confidence Software Technologies of the Ministry of Education, Peking University, Beijing 100871, China 3Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing 100190, China 4Department of Management Science and engineering, Tsinghua University, Beijing 100084, 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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NUITS: A Novel User Interface for Efficient keyword Search over databases

NUITS: A Novel User Interface for Efficient Keyword Search o...

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32nd International Conference on Very Large data Bases, VLDB 2006

作者： Wang, Shan Peng, Zhaohui Zhang, Jun Qin, Lu Wang, Sheng Yu, Jeffrey Xu Ding, Bolin School of Information Renmin Univ. of China Key Laboratory of Data Engineering and Knowledge Engineering MOE of China Beijing China Department of Systems Engineering and Engineering Management The Chinese Univ. of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)1595933859

The integration of database and information retrieval techniques provides users with a wide range of high quality services. We present a prototype system, called NUITS, for efficiently processing keyword queries on top of a relational database. Our NUITS allows users to issue simple keyword queries as well as advanced keyword queries with conditions. The efficiency of keyword query processing and the user-friendly result display will also be addressed in this paper. Copyright 2006 VLDB Endowment, ACM

关键词： Query processing

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The Research on the Algorithms of keyword Search in Relational database

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2008年 4977卷 134-143页

作者： Li, Peng Zhu, Qing Wang, Shan Key Laboratory of Data Engineering and Knowledge Engineering School of Information Renmin University of China Beijing100872 China

ISBN: (纸本)354089375X

With the development of relational database, people require better database not only in the aspect of database performance, but also in the aspect of the database’s interactive ability. So that the database is much more friendly than just before and it is possible for a common user who do not have any special knowledge on database can access the database, without knowing the schema of database and writing intricate SQL. For the reason that the information retrieval on the web has developed well to some extent, when we develop the technology of keyword search in relational database, we can draw some ideas from information retrieve. But the great differences between the text database on the web and the relational database also bring some new challenges: 1) The answer needed by user is not only one tuple in database, but the tuple sets consisting of the tuple connect from different table using the "primary key-foreign key" relationship. 2)The results of the evaluation criteria is more important, because it is directly related to the effectiveness of Search System. 3)The structure of relational database is much more intricate than text database, and the algorithms of information retrieval are not fit the relational database. So in this paper, we introduce a novel keyword search algorithm and a modified criteria of evaluating answers in order to enhance efficiency of the keyword search and return much more effective information to users, finally, the search algorithm’s performance is tested and evaluated. © Springer-Verlag Berlin Heidelberg 2008

关键词： Information retrieval

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RESIDUAL ATTENTION BLOCK SEARCH FOR LIGHTWEIGHT IMAGE SUPER-RESOLUTION

RESIDUAL ATTENTION BLOCK SEARCH FOR LIGHTWEIGHT IMAGE SUPER-...

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2021 IEEE International Conference on Multimedia and Expo, ICME 2021

作者： Liao, Wenrui Zhao, Zhong-Qiu Shen, Hao Tian, Weidong School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology China Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology China

ISBN: (纸本)9781665438643

Recently, lightweight neural networks with different manual designs have presented a promising performance in single image super-resolution (SR). However, these designs rely on too much expert experience. To address this issue, we focus on searching a lightweight block for efficient and accurate image SR. Due to the frequent use of various residual blocks and attention mechanisms in SR methods, we propose the residual attention search block (RASB) which combines an operation search block (OSB) with an attention search block (ASB). The former is used to explore the suitable operation at the proper position, and the latter is applied to discover the optimal connection of various attention mechanisms. Moreover, we build the modified residual attention network (MRAN) with stacked found blocks and a refinement module. Extensive experiments demonstrate that our MRAN achieves a better trade-off against the state-of-the-art methods in terms of accuracy and model complexity. © 2021 IEEE

关键词： Economic and social effects

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Efficient processing of global Top-k aggregate queries in uncertain database

Efficient processing of global Top-k aggregate queries in un...

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2009 International Conference on Information engineering and Computer Science, ICIECS 2009

作者： Xing, Xianli Liu, Dexi Principal's Office Jiangxi University of Finance and Economics Nanchang China School of Information Technology Jiangxi University of Finance and Economics Jiangxi Key Laboratory of Data and Knowledge Engineering Nanchang China

ISBN: (纸本)9781424449941

Top-k queries in uncertain databases are quite popular and useful due to its wide application usage. However, compared to Top-k in traditional databases, queries over uncertain database are more complicated because of the existence of exponential possible worlds. A Top-k aggregate query ranks groups of tuples by their aggregate values, sum or average for example, and returns k groups with the highest aggregate values. As a powerful semantic of Top-k, Global Top-k, returns k highest-ranked tuples according to their probabilities of being in the Top-k answers in possible worlds. We propose a dynamic programming based method to process Global Top-k aggregate queries in uncertain database, where the number of retrieved tuples and group states generated on these tuples are minimized. Experiment results show that our algorithm is effective. ©2009 IEEE.

关键词： Dynamic programming

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HUSS:A Heuristic Method for Understanding the Semantic Structure of Spreadsheets

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data Intelligence 2023年第3期5卷 537-559页

作者： Xindong Wu Hao Chen Chenyang Bu Shengwei Ji Zan Zhang Victor S.Sheng Key Laboratory of Knowledge Engineering with Big Data(the Ministry of Education of China) Hefei University of TechnologyChinaSchool of Computer Science and Information EngineeringHefei University of TechnologyHefeiChina Research Institute of Artificial Intelligence Zhejiang LabHangzhouChina Department of Computer Science Texas Tech UniversityLubbockTX 79409USA

Spreadsheets contain a lot of valuable data and have many practical *** key technology of these practical applications is how to make machines understand the semantic structure of spreadsheets,e.g.,identifying cell function types and discovering relationships between cell *** existing methods for understanding the semantic structure of spreadsheets do not make use of the semantic information of cells.A few studies do,but they ignore the layout structure information of spreadsheets,which affects the performance of cell function classification and the discovery of different relationship types of cell *** this paper,we propose a Heuristic algorithm for Understanding the Semantic Structure of spreadsheets(HUSS).Specifically,for improving the cell function classification,we propose an error correction mechanism(ECM)based on an existing cell function classification model[11]and the layout features of *** improving the table structure analysis,we propose five types of heuristic rules to extract four different types of cell pairs,based on the cell style and spatial location *** experimental results on five real-world datasets demonstrate that HUSS can effectively understand the semantic structure of spreadsheets and outperforms corresponding baselines.

关键词： Spreadsheet semantic structure Information extraction Heuristics Cell function analysis Table structure analysis

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