检索结果-内蒙古大学图书馆

WATuning:A Workload-Aware Tuning System with Attention-Based Deep Reinforcement Learning

Journal of Computer Science & Technology 2021年第4期36卷 741-761页

作者： Jia-Ke Ge Yan-Feng Chai Yun-Peng Chai Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education Renmin University of China Beijing 100872China School of Information Renmin University of ChinaBeijing 100872China College of Computer Science and Technology Taiyuan University of Science and TechnologyTaiyuan 030027China

Configuration tuning is essential to optimize the performance of systems(e.g.,databases,key-value stores).High performance usually indicates high throughput and low *** present,most of the tuning tasks of systems are performed artificially(e.g.,by database administrators),but it is hard for them to achieve high performance through tuning in various types of systems and in various *** recent years,there have been some studies on tuning traditional database systems,but all these methods have some *** this article,we put forward a tuning system based on attention-based deep reinforcement learning named WATuning,which can adapt to the changes of workload characteristics and optimize the system performance efficiently and ***,we design the core algorithm named ATT-Tune for WATuning to achieve the tuning task of *** algorithm uses workload characteristics to generate a weight matrix and acts on the internal metrics of systems,and then ATT-Tune uses the internal metrics with weight values assigned to select the appropriate ***,WATuning can generate multiple instance models according to the change of the workload so that it can complete targeted recommendation services for different types of ***,WATuning can also dynamically fine-tune itself according to the constantly changing workload in practical applications so that it can better fit to the actual environment to make *** experimental results show that the throughput and the latency of WATuning are improved by 52.6%and decreased by 31%,respectively,compared with the throughput and the latency of CDBTune which is an existing optimal tuning method.

关键词： attention mechanism auto-tuning system reinforcement learning(RL) workload-aware

来源：评论

学校读者我要写书评

暂无评论

Accuracy estimation of link-based similarity measures and its application

引用

Frontiers of Computer Science 2016年第1期10卷 113-123页

作者： Yinglong ZHANG Cuiping LI Chengwang XIE Hong CHEN School of Software East China Jiaotong University Nanchang 330045 China Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education and Department of Computer Science Renmin University of China Beijing 100872 China Intelligent Optimization and Information Processing Laboratory East China Jiaotong University Nanchang 330013 China

Link-based similarity measures play a significant role in many graph based applications. Consequently, mea- suring node similarity in a graph is a fundamental problem of graph data mining. Personalized PageRank （PPR） and Sim- Rank （SR） have emerged as the most popular and influen- tial link-based similarity measures. Recently, a novel link- based similarity measure, penetrating rank （P-Rank）, which enriches SR, was proposed. In practice, PPR, SR and P-Rank scores are calculated by iterative methods. As the number of iterations increases so does the overhead of the calcula- tion. The ideal solution is that computing similarity within the minimum number of iterations is sufficient to guaran- tee a desired accuracy. However, the existing upper bounds are too coarse to be useful in general. Therefore, we focus on designing an accurate and tight upper bounds for PPR, SR, and P-Rank in the paper. Our upper bounds are designed based on the following intuition： the smaller the difference between the two consecutive iteration steps is, the smaller the difference between the theoretical and iterative similar- ity scores becomes. Furthermore, we demonstrate the effec- tiveness of our upper bounds in the scenario of top-k similar nodes queries, where our upper bounds helps accelerate the speed of the query. We also run a comprehensive set of exper- iments on real world data sets to verify the effectiveness and efficiency of our upper bounds.

关键词： personalized PageRank SimRank P-Rank up-per bound

来源：评论

学校读者我要写书评

暂无评论

Stop thinking, start tagging: Tag semantics emerge from collaborative verbosity 10

Stop thinking, start tagging: Tag semantics emerge from coll...

引用

19th International World Wide Web Conference, WWW2010

作者： Körner, Christian Benz, Dominik Hotho, Andreas Strohmaier, Markus Stumme, Gerd Knowledge Management Institute Graz University of Technology Graz Austria Knowledge and Data Engineering Group University of Kassel Kassel Germany Data Mining and Information Retrieval Group University of Würzburg Würzburg Germany Knowledge Management Institute Know-Center Graz University of Technology Graz Austria

ISBN: (纸本)9781605587998

Recent research provides evidence for the presence of emergent semantics in collaborative tagging systems. While several methods have been proposed, little is known about the factors that influence the evolution of semantic structures in these systems. A natural hypothesis is that the quality of the emergent semantics depends on the pragmatics of tagging: Users with certain usage patterns might contribute more to the resulting semantics than others. In this work, we propose several measures which enable a pragmatic differentiation of taggers by their degree of contribution to emerging semantic structures. We distinguish between categorizers, who typically use a small set of tags as a replacement for hierarchical classification schemes, and describers, who are annotating resources with a wealth of freely associated, descriptive keywords. To study our hypothesis, we apply semantic similarity measures to 64 different partitions of a real-world and large-scale folksonomy containing different ratios of categorizers and describers. Our results not only show that "verbose" taggers are most useful for the emergence of tag semantics, but also that a subset containing only 40% of the most 'verbose' taggers can produce results that match and even outperform the semantic precision obtained from the whole dataset. Moreover, the results suggest that there exists a causal link between the pragmatics of tagging and resulting emergent semantics. This work is relevant for designers and analysts of tagging systems interested (i) in fostering the semantic development of their platforms, (ii) in identifying users introducing "semantic noise", and (iii) in learning ontologies. © 2010 International World Wide Web Conference Committee (IW3C2).

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Face-to-face contacts at a conference: Dynamics of communities and roles

Face-to-face contacts at a conference: Dynamics of communiti...

引用

2nd International Workshop on Modeling and Mining Ubiquitous Social Media, MSM 2011, MUSE 2011

作者： Atzmueller, Martin Doerfel, Stephan Hotho, Andreas Mitzlaff, Folke Stumme, Gerd University of Kassel Knowledge and Data Engineering Group Wilhelmshöher Allee 73 34121 Kassel Germany University of Würzburg Data Mining and Information Retrieval Group Am Hubland 97074 Würzburg Germany

ISBN: (纸本)9783642336836

This paper focuses on the community analysis of conference participants using their face-to-face contacts, visited talks, and tracks in a social and ubiquitous conferencing scenario. We consider human face-to-face contacts and perform a dynamic analysis of the number of contacts and their lengths. On these dimensions, we specifically investigate user-interaction and community structure according to different special interest groups during a conference. Additionally, using the community information, we examine different roles and their characteristic elements. The analysis is grounded using real-world conference data capturing community information about participants and their face-to-face contacts. The analysis results indicate, that the face-to-face contacts show inherent community structure grounded using the special interest groups. Furthermore, we provide individual and community-level properties, traces of different behavioral patterns, and characteristic (role) profiles. © 2012 Springer-Verlag.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

ASAWA: An automatic partition key selection strategy

ASAWA: An automatic partition key selection strategy

引用

15th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2013

作者： Wang, Xiaoyan Chen, Jinchuan Du, Xiaoyong School of Information Renmin University of China China School of Information and Electrical Engineering Ludong University China Key Laboratory of Data Engineering and Knowledge Engineering MOE China

ISBN: (纸本)9783642374005

With the rapid increase of data volume, more and more applications have to be implemented in a distributed environment. In order to obtain high performance, we need to carefully divide the whole dataset into multiple partitions and put them into distributed data nodes. During this process, the selection of partition key would greatly affect the overall performance. Nevertheless, there are few works addressing this topic. Most previous projects on data partitioning either utilize a simple strategy, or rely on a commercial database system, to choose partition keys. In this work, we present an automatic partition key selection strategy called ASAWA. It chooses partition keys according to the analysis on both dataset and workload schemas. In this way, intimate tuples, i.e. co-appearing in queries frequently, would be probably put into the same partition. Hence the cross-node joins could be greatly reduced and the system performance could be improved. We conduct a series of experiments over the TPC-H datasets to illustrate the effectiveness of the ASAWA strategy. © 2013 Springer-Verlag.

关键词： data handling

来源：评论

学校读者我要写书评

暂无评论

An approach for personalized tag recommendation based on interest transfer model

An approach for personalized tag recommendation based on int...

引用

9th Web information Systems and Applications Conference, WISA 2012

作者： Liu, Yue Yang, Nan Yang, Gang School of Information Renmin University of China Bejing China Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Bejing China

ISBN: (纸本)9781467330541

Recently, social tagging systems become more and more popular in many Web 2.0 applications. In such systems, Users are allowed to annotate a particular resource with a freely chosen a set of tags. These user-generated tags can represent users' interests more concise and closer to human understanding. Interests will change over time. Thus, how to describe users' interests and interests transfer path become a big challenge for personalized recommendation systems. In this approach, we propose a variable-length time interval division algorithm and user interest model based on time interval. Then, in order to draw users' interests transfer path over a specific time period, we suggest interest transfer model. After that, we apply a classical community partition algorithm in our approach to separate users into communities. Finally, we raise a novel method to measure users' similarities based on interest transfer model and provide personalized tag recommendation according to similar users' interests in their next time intervals. Experimental results demonstrate the higher precision and recall with our approach than classical user-based collaborative filtering methods. © 2012 IEEE.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

Cluster labeling extraction and ranking feature selection for high quality XML pseudo relevance feedback fragments set

Cluster labeling extraction and ranking feature selection fo...

引用

9th International Conference on Advanced data Mining and Applications, ADMA 2013

作者： Zhong, Minjuan Wan, Changxuan Liu, Dexi Liao, Shumei Luo, Siwen School of Information Technology Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9783642539169

In traditional pseudo feedback, the main reason of the topic drift is the low quality of the feedback source. Clustering search results is an effective way to improve the quality of feedback set. For XML data, how to effectively perform clustering algorithm and then identify good xml fragments from the clustering results is a intricate problem. This paper mainly focus on the latter problem. Based on k-mediod clustering results, This work firstly proposes an cluster label extraction method to select candidate relevant clusters. Secondly, multiple ranking features are introduced to assist the related xml fragments identification from the candidate clusters. Top N fragments compose the high quality pseudo feedback set finally. Experimental results on standard INEX test data show that in one hand, the proposed cluster label extraction method could obtain proper cluster key terms and lead to appropriate candidate cluster selection. On the other hand, the presented ranking features are beneficial to the relevant xml fragments identification. The quality of feedback set is ensured. © 2013 Springer-Verlag.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

Factor decomposition of regional carbon emissions from energy consumption for China

Factor decomposition of regional carbon emissions from energ...

引用

3rd International Conference on Energy and Environmental Protection, ICEEP 2014

作者： Qi, Ya-Wei School of Information Technology Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9783038351375

This paper calculates the carbon emissions from energy consumption of 30 provinces in China through 2000-2010, and research correlation of factors such as regional economic gap and regional characteristics of carbon emissions in the process of regional economic coordinated development. The LMDI decomposition model is used to decompose the growth rate of China's carbon emissions into 4 types of driving factors, i.e. GDP, industrial pollutants emission intensity, industrial structure and imbalance of regional economic development, to analyze influence of scale effect, technical effect, industrial structure effect and regional spatial structure effect on carbon emissions in the process of China's regional economic development. The results show that: The scale effect is determinants of carbon emissions increasing. The technical effect is the most important force to inhibit the increment of carbon emissions. Industrial structure effect and regional spatial structure effect on carbon emissions are not yet stable, but have a certain pull impact on increasing carbon emissions. © (2014) Trans Tech Publications, Switzerland.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

Can web news media sentiments improve stock trading signal prediction? 18

Can web news media sentiments improve stock trading signal p...

引用

18th Pacific Asia Conference on information Systems, PACIS 2014

作者： Lin, Nana Xu, Wei Zhang, Xinwei Lv, Siqi School of Information Renmin University of China Beijing China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China School of Information Beijing China

The technical analysis and machine learning have been integrated in stock trading signal forecasting. And it has been proved that there are some weaknesses in technical analysis because of the complex environment in the stock market. In our prediction system, web news media sentiment analysis is regarded as a supplementary way to cover the shortage of technical analysis. It is considered to bring the stock market sentiment which reflects the subjective information of investors into the prediction system. Web news media sentiment indicators (WNMS) are designed to bring the information about stock market sentiment in our system. The WNMS is generated by analyzing the variance of sentiment elements from the news in the Stock Timely Rain Sector of Sina Finance and Economics Website and it is imported into the prediction system as features combined with common feature indicators (CFI). GMKL is applied to establish the relationship between the trading signals generated by piecewise linear representation (PLR) and the features of the trading signals (SCFI). Comparative experiments are adopted in nine stocks from Shanghai and Shenzhen Stock Exchange to determine the effect of PLR-GMKL and WNMS in prediction. From the aspects of the prediction accuracy and the profit, the final comparative results show that the PLR-GMKL model performs better than the PLR-WSVM model. And the prediction system performs best when adding WNMS into features and using PLRGMKL model.

关键词： Financial markets

来源：评论

学校读者我要写书评

暂无评论

Research on government information sharing model using blockchain technology 10

Research on government information sharing model using block...

引用

10th International Conference on information Technology in Medicine and Education, ITME 2019

作者： Zhang, Yiwei Deng, Sanhong Zhang, Yue Kong, Jia School of Information Management Nanjing University Jiangsu Key Laboratory of Data Engineering and Knowledge Service. Nanjing China

ISBN: (纸本)9781728139173

Research Purpose: The distributed, traceable and security of blockchain technology are applicable to the construction of new government information resource models, which could eliminate the barn effect and trust in government information sharing, as well as promoting the transformation of government affairs from management to service, it is also of great significance to the sharing of government information and construction of service-oriented e-government. Propose Methods: By analyzing the current problems of government information sharing, combined with literature research, this paper proposes the theoretical framework and advantages of blockchain technology applied to government information management and sharing, expounds the blockchain-based solution, it also constructs a government information sharing model based on blockchain, and gives implementation strategies at the technical and management levels. Results and Conclusion: The government information sharing model based on the blockchain solution and the transparency of government information can be used as a research framework for information interaction analysis between the government and users. It can also promote the construction and development of information sharing for Chinese government, as well as providing unified information sharing solution at the departmental and regional levels for e-government. © 2019 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：