检索结果-内蒙古大学图书馆

International Conference on Management of e-Commerce and e-Government, ICMECG

作者： Wu Rui Liao Guoqiong Di Guoqiang School of Information Technology Jiangxi University of Finance and Economics Nanchang China School of Information Technology Jiangxi Key Laboratory of Data and Knowledge Engineering Nanchang China

Filtering redundancy data is an important task of radio frequency identification (RFID) middleware. In order to ensure RFID middleware can effectively filter the time redundant data and identify tagged object location change timely, this paper proposed a Temporal-Spatial bloom filter based on the sliding window model. The filter extends the one-dimension array in the standard bloom filter to a two-dimension array. Meanwhile, in order to guarantee the false positive rate doesn't increase due to the reason that the storage unit of the filter becomes full, we proposed a random decay strategy for deleting the expiration elements. The experimental results show that TSBF algorithm can filter time redundant data effectively and had a good performance to deal with location movement.

关键词： Radiofrequency identification Filtering algorithms Information filters data models Algorithm design and analysis

来源：评论

学校读者我要写书评

暂无评论

Automatic data distribution in large-scale OLTP applications

International Journal of Database Theory and Application

引用

International Journal of database Theory and Application 2014年第4期7卷 37-46页

作者： Wang, Xiaoyan Fan, Xu Chen, Jinchuan Du, Xiaoyong Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE Beijing 100872 China School of Information and Electrical Engineering Ludong University Yantai 264025 China School of Information Renmin University of China Beijing 100872 China

With the dramatic increase of data volume, automatic data distribution has been one of the key techniques and intractable problem for distributed systems. This work summarizes the problem of data distribution and abstracts it as a general triangle model called DaWN. Based on data and workload analysis, it presents a novel strategy called ADDS for automatic data distribution in OLTP applications. According to the results of a series of experiments over TPC-C datasets and transactions, the proposed approach shows effective improvements.© 2014 SERSC.

关键词： data handling

来源：评论

学校读者我要写书评

暂无评论

Author Correction: The power of genetic diversity in genome-wide association studies of lipids

引用

Nature 2023年第7965期618卷 E19-E20页

作者： Sarah E Graham Shoa L Clarke Kuan-Han H Wu Stavroula Kanoni Greg J M Zajac Shweta Ramdas Ida Surakka Ioanna Ntalla Sailaja Vedantam Thomas W Winkler Adam E Locke Eirini Marouli Mi Yeong Hwang Sohee Han Akira Narita Ananyo Choudhury Amy R Bentley Kenneth Ekoru Anurag Verma Bhavi Trivedi Hilary C Martin Karen A Hunt Qin Hui Derek Klarin Xiang Zhu Gudmar Thorleifsson Anna Helgadottir Daniel F Gudbjartsson Hilma Holm Isleifur Olafsson Masato Akiyama Saori Sakaue Chikashi Terao Masahiro Kanai Wei Zhou Ben M Brumpton Humaira Rasheed Sanni E Ruotsalainen Aki S Havulinna Yogasudha Veturi QiPing Feng Elisabeth A Rosenthal Todd Lingren Jennifer Allen Pacheco Sarah A Pendergrass Jeffrey Haessler Franco Giulianini Yuki Bradford Jason E Miller Archie Campbell Kuang Lin Iona Y Millwood George Hindy Asif Rasheed Jessica D Faul Wei Zhao David R Weir Constance Turman Hongyan Huang Mariaelisa Graff Anubha Mahajan Michael R Brown Weihua Zhang Ketian Yu Ellen M Schmidt Anita Pandit Stefan Gustafsson Xianyong Yin Jian'an Luan Jing-Hua Zhao Fumihiko Matsuda Hye-Mi Jang Kyungheon Yoon Carolina Medina-Gomez Achilleas Pitsillides Jouke Jan Hottenga Gonneke Willemsen Andrew R Wood Yingji Ji Zishan Gao Simon Haworth Ruth E Mitchell Jin Fang Chai Mette Aadahl Jie Yao Ani Manichaikul Helen R Warren Julia Ramirez Jette Bork-Jensen Line L Kårhus Anuj Goel Maria Sabater-Lleal Raymond Noordam Carlo Sidore Edoardo Fiorillo Aaron F McDaid Pedro Marques-Vidal Matthias Wielscher Stella Trompet Naveed Sattar Line T Møllehave Betina H Thuesen Matthias Munz Lingyao Zeng Jianfeng Huang Bin Yang Alaitz Poveda Azra Kurbasic Claudia Lamina Lukas Forer Markus Scholz Tessel E Galesloot Jonathan P Bradfield E Warwick Daw Joseph M Zmuda Jonathan S Mitchell Christian Fuchsberger Henry Christensen Jennifer A Brody Mary F Feitosa Mary K Wojczynski Michael Preuss Massimo Mangino Paraskevi Christofidou Niek Verweij Jan W Benjamins Jorgen Engmann Rachel L Kember Roderick C Slieker Ken Sin Lo Nuno R Zilhao Phuong Le Marcus E Kleber Graciela E Delgado Shaofeng Huo Dai Department of Internal Medicine Division of Cardiology University of Michigan Ann Arbor MI USA. VA Palo Alto Health Care System Palo Alto CA USA. Department of Medicine Division of Cardiovascular Medicine Stanford University School of Medicine Stanford CA USA. Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Department of Biostatistics and Center for Statistics Genetics University of Michigan Ann Arbor MI USA. Department of Genetics Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Clinical Pharmacology William Harvey Research Institute Barts and The London School of Medicine and Dentistry Queen Mary University of London London UK. Endocrinology Boston Children's Hospital Boston MA USA. Medical and Population Genetics Broad Institute Cambridge MA USA. Department of Genetic Epidemiology University of Regensburg Regensburg Germany. McDonnell Genome Institute and Department of Medicine Washington University St Louis MO USA. Department of Precision Medicine Division of Genome Science National Institute of Health Cheongju-si South Korea. Tohoku Medical Megabank Organization Tohoku University Sendai Japan. Sydney Brenner Institute for Molecular Bioscience Faculty of Health Sciences University of the Witwatersrand Johannesburg South Africa. Center for Research on Genomics and Global Health National Human Genome Research Institute National Institutes of Health Bethesda MD USA. Blizard Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Wellcome Sanger Institute Hinxton UK. Department of Epidemiology Emory University Rollins School of Public Health Atlanta GA USA. Atlanta VA Health Care System Decatur GA USA. Malcolm Randall VA Medical Center Gainesville FL USA. Division of Vascular Sur

来源：评论

学校读者我要写书评

暂无评论

Improved head-driven statistical models for natural language parsing

引用

Journal of Central South University 2013年第10期20卷 2747-2752页

作者：袁里驰 School of Information Technology Jiangxi University of Finance and Economics Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics

Head-driven statistical models for natural language parsing are the most representative lexicalized syntactic parsing models, but they only utilize semantic dependency between words, and do not incorporate other semantic information such as semantic collocation and semantic category. Some improvements on this distinctive parser are presented. Firstly, "valency" is an essential semantic feature of words. Once the valency of word is determined, the collocation of the word is clear, and the sentence structure can be directly derived. Thus, a syntactic parsing model combining valence structure with semantic dependency is purposed on the base of head-driven statistical syntactic parsing models. Secondly, semantic role labeling(SRL) is very necessary for deep natural language processing. An integrated parsing approach is proposed to integrate semantic parsing into the syntactic parsing process. Experiments are conducted for the refined statistical parser. The results show that 87.12% precision and 85.04% recall are obtained, and F measure is improved by 5.68% compared with the head-driven parsing model introduced by Collins.

关键词： valence structure semantic dependency head-driven statistical syntactic parsing semantic role labeling

来源：评论

学校读者我要写书评

暂无评论

Analyzing Information Needs of Elderly People: A Survey in Chinese Rural Community

Analyzing Information Needs of Elderly People: A Survey in C...

引用

2014年管理与服务科学国际学术会议

作者： Chunfang Zou Ping Zhou School of business administration Jiangxi University of Finance and Economics School of Information Technology Jiangxi University of Finance and Economics Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics

A survey about the information needs of elderly people could find out the information required to address the needs of the aged in a community. Analyzing data collected from 600 elderly people through

关键词：

来源：评论

学校读者我要写书评

暂无评论

Distance-based feature selection from probabilistic data

Distance-based feature selection from probabilistic data

引用

14th International Conference on Web-Age Information Management, WAIM 2013

作者： Zhao, Tingting Pei, Bin Zhao, Suyun Chen, Hong Li, Cuiping Key Lab of Data Engineering and Knowledge Engineering Ministry of Education China Department of Computer Science Renmin University of China China

ISBN: (纸本)9783642385612

Feature selection is a powerful tool of dimension reduction from datasets. In the last decade, more and more researchers have paid attentions on feature selection. Further, some researchers begin to focus on feature selection from probabilistic datasets. However, in the existing method of feature selection from probabilistic data, the distance hidden in probabilistic data is neglected. In this paper, we design a new distance measure to select informative feature from probabilistic databases, in which both the distance and randomness in the data are considered. And then, we propose a feature selection algorithm based on the new distance and develop two accelerative algorithms to boost the computation. Furthermore, we introduce a parameter into the distance to reduce the sensitivity to noise. Finally, the experimental results verify the effectiveness of our algorithms. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Random processes

来源：评论

学校读者我要写书评

暂无评论

Improved factor analysis algorithm in factor spaces

Improved factor analysis algorithm in factor spaces

引用

2014 International Conference on Informatics, Networking and Intelligent Computing(INIC 2014)

作者： H.D.Wang Y.Shi P.Z.Wang H.T.Liu Key Research Lab on Big Data Mining and Knowledge Management Chinese Academy of SciencesBeijingChina Research Center on Fictitious Economy & Data ScienceChinese Academy of SciencesBeijingChina School of Mathematical SciencesUniversity of Chinese Academy of Sciences Institute of Intelligent Engineering and Mathematics Liaoning Technical University

In order to further improve the velocity and the utilization of information contained in samples,an improved version of the Factor Analysis Algorithm(FAA) in factor spaces is presented in this *** primary algorithm is considered from the whole classes during the selection of the next classified factor,by which a smaller decision domain is generated than that generated by considering from each class,and the deletion of the decision domain is critical in decreasing calculation and increasing the velocity of the ***,based on inheriting the merits of the initial algorithm,the pushing way by each column is changed into that by each class during the selection of the next classified *** change not only decreases the calculation,but also improves the utilization of the sample *** testing results also indicate that the improvement is significant and the testing accuracy rate and velocity are both better than the primary algorithm.

关键词： Factor spaces factor analysis decision domain time complexity

来源：评论

学校读者我要写书评

暂无评论

Classifying tag relevance with relevant positive and negative examples 13

Classifying tag relevance with relevant positive and negativ...

引用

21st ACM International Conference on Multimedia, MM 2013

作者： Li, Xirong Snoek, Cees G. M. Key Lab of Data Engineering and Knowledge Engineering Renmin University of China China Intelligent Systems Lab Amsterdam University of Amsterdam Netherlands

ISBN: (纸本)9781450324045

Image tag relevance estimation aims to automatically deter- mine what people label about images is factually present in the pictorial content. Different from previous works, which either use only positive examples of a given tag or use pos- itive and random negative examples, we argue the impor- Tance of relevant positive and relevant negative examples for tag relevance estimation. We propose a system that se- lects positive and negative examples, deemed most relevant with respect to the given tag from crowd-annotated images. While applying models for many tags could be cumbersome, our system trains efficient ensembles of Support Vector Ma- chines per tag, enabling fast classification. Experiments on two benchmark sets show that the proposed system com- pares favorably against five present day methods. Given extracted visual features, for each image our system can pro- cess up to 3,787 tags per second. The new system is both effective and efficient for tag relevance estimation. Copyright © 2013 ACM.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

Top-k neighborhood dominating query

Top-k neighborhood dominating query

引用

18th International Conference on database Systems for Advanced Applications, DASFAA 2013

作者： Xie, Xike Lu, Hua Chen, Jinchuan Shang, Shuo Department of Computer Science Aalborg University Denmark Key Labs of Data Engineering and Knowledge Engineering MOE Renmin University of China China

ISBN: (纸本)9783642374869

In many real-life applications, spatial objects are associated with multiple non-spatial attributes. For example, a hotel may have price and rating in addition to its geographic location. In traditional spatial databases, spatial objects are often ranked solely based on their distance to a given query location, e.g., in a nearest neighbor search. In another line of research, domination based skyline queries are used to return best objects according to multi-criteria on non-spatial attributes. In this paper, we study how to rank spatial objects with respect to their non-spatial attributes within their spatial neighborhoods. To enable a general ranking, we design a ranking function that inherits the advantages of dominance relationship and integrates them with spatial proximity. Further, we propose an effective index structure, and a branch and bound solution that executes the ranking efficiently via the index. We conduct extensive empirical studies on real and synthetic datasets. The results demonstrate the high efficiency of our proposal compared to straightforward alternatives. © Springer-Verlag 2013.

关键词： Nearest neighbor search

来源：评论

学校读者我要写书评

暂无评论

Efficient SPARQL query evaluation via automatic data partitioning

Efficient SPARQL query evaluation via automatic data partiti...

引用

18th International Conference on database Systems for Advanced Applications, DASFAA 2013

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

ISBN: (纸本)9783642374494

The volume of RDF data increases very fast within the last five years, e.g. the Linked Open data cloud grows from 2 billions to 50 billions of RDF triples. With its wonderful scalability, cloud computing platform like Hadoop is a good choice for processing queries over large data sets. Previous works on evaluating SPARQL queries with Hadoop mainly focus on reducing the number of joins through careful split of HDFS files and algorithms for generating Map/Reduce jobs. However, the way of partitioning RDF data could also affect the performance. Specifically, a good partitioning will greatly reduce or even totally avoid cross-node joins and significantly reduce the cost of query evaluation. Based on HadoopDB, this work processes SPARQL queries in a hybrid architecture where Map/Reduce takes charge of the computing tasks and an RDF query engine, RDF-3X, stores the data and evaluates join operations over local data. Based on analysis of query work-loads, we propose a novel algorithm for automatically partitioning RDF data. We also present an approximate solution to physically place the partitions in order to reduce data redundancy. All the proposed approaches are evaluated by extensive experiments over large RDF data sets. © Springer-Verlag 2013.

关键词： Resource Description Framework (RDF)

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：