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A new BP algorithm for network marketing performance evaluation of agricultural products

Journal of Applied Sciences 2013年第20期13卷 4332-4335页

作者： Zou, Chun-Fang Huang, Li-Juan School of of Business Administration Jiangxi University of Finance and Economics 330013 Nanchang Jiangxi China School of Information Technology Jiangxi University of Finance and Economics 330013 Nanchang Jiangxi China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics 330013 Nanchang Jiangxi China

Network marketing performance evaluation can sum up and improve the network marketing activities for network enterprises. So, how to evaluate network marketing performance has become a matter of concern in the field related. The study mainly takes agricultural products for example and presents a new algorithm for evaluating network marketing performance based on improved BP neural network algorithm. First, a evaluation indicator system for evaluating network marketing performance of agricultural products is constructed;Second the study analyzes the reasons of the defects of BP neural network algorithm and then designs a new BP algorithm and improves it through changing its learning rate to speed up the calculation and simplify the structure of the original BP algorithm;Finally, the improved algorithm is realized with three e_commerce enterprises are taken for examples to evaluate the network marketing performance and verify the validity and feasibility of the model and the experimental results show that the model can evaluate the network marketing performance of different enterprises practically. © 2013 Asian Network for Scientific Information.

关键词： Agricultural products

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Top-k entities query processing on uncertainly fused multi-sensory data

Top-k entities query processing on uncertainly fused multi-s...

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作者： Liu, Dexi Wan, Changxuan Xiong, Naixue Park, Jong Hyuk Rho, Seungmin Jiangxi Key Laboratory of Data and Knowledge Engineering School of Information Technology Jiangxi University of Finance and Economics Nanchang China Department of Computer Science Georgia State University Atlanta GA United States Department of Computer Science and Engineering Seoul National University of Science and Technology Seoul Korea Republic of School of Electrical Engineering Korea University Seoul Korea Republic of

Sensor fusion is the combining of sensory data from disparate sources such that the resulting information is in some sense better than would be possible when these sources were used individually. The natural uncertainty exists in these data because sensors are not precise enough. Hence, the intuitive method to store this kind of data is using uncertain database. Finding the top-k entities according to one or more attributes is a powerful technique when the uncertain database contains large quantity of data. However, compared to top-k in traditional databases, queries over uncertain database are more complicated because of the existence of exponential possible worlds. We propose a method to process entity-based global top-k aggregate queries in uncertain database, which returns the top-k entities that have the highest aggregate value. Our method has two levels, entity state generation and G-topk-E query processing. In the former level, entity states, which satisfy the properties of x-tuple, are generated one after the other according to their aggregate values, while in the latter level, dynamic programming-based global top-k entity query processing is employed to return the answers. Comprehensive experiments on different data sets demonstrate the effectiveness of the proposed solutions. © 2012 Springer-Verlag London Limited.

关键词： Query processing

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A dominating set based approach to identify effective leader group of social network

A dominating set based approach to identify effective leader...

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19th International Computing and Combinatorics Conference, COCOON 2013

作者： Kim, Donghyun Li, Deying Asgari, Omid Li, Yingshu Tokuta, Alade O. Dept. of Mathematics and Computer Science North Carolina Central University Durham NC 27707 United States Key Laboratory of Data Engineering and Knowledge Engineering School of Information Renmin University of China Renmin 100872 China Dept. of Computer Science Georgia State University Atlanta GA 30303 United States

ISBN: (纸本)9783642387678

Very recently, the study of social networks has received a huge attention since we can learn and understand many hidden properties of our society. This paper investigates the potential of social network analysis to select an effective leadership group of a society. Based on our real life observation, we establish three essential requirements for an effective leadership group, namely Influenceability, Partisanship, and Bipartisanship. Then, we formulate the problem of finding a minimum size leader group satisfying the three requirements as the minimum connected k-core dominating set problem (MCkCDSP), and show its NP-hardness. In addition, we introduce an extension of MCkCDSP, namely MCkCDSP-C, which assumes the society has a number of communities and requires at least one representative from each community should be in the leadership. At last, we propose an approximation algorithm for a subclass of MCkCDSP with k = 2, and show an α-approximation algorithm of MCkCDSP can be used to obtain an α-approximation algorithm of MCkCDSP-C. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Approximation algorithms

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Design of greenhouse gases remote sensing monitoring and validation system and the key technologies

Design of greenhouse gases remote sensing monitoring and val...

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34th Asian Conference on Remote Sensing 2013, ACRS 2013

作者： Miao, Ru Lu, Ning Wang, Juanle Yao, Ling Institute of Data and Knowledge Engineering College of Computer and Information Engineering Henan University Jin Ming Avenue Kaifeng Henan 475004 China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences 11A Datun Road Chaoyang District Beijing 100101 China

ISBN: (纸本)9781629939100

Greenhouse gases remote sensing monitoring system is implementation of greenhouse gases remote sensing applied technologies. This paper discusses the business application mode, operation scheme and application technology system of greenhouse gases remote sensing monitoring based on multi-source remote sensing data. The system analysis of greenhouse gases remote sensing monitoring is introduced in this paper, which include data flow analysis, transaction flow analysis, system structure analysis and core functions analysis. The prototype system is constructed using .NET, ArcEngine and IDL mixing programming language and its application example are presented. System application results show that this system meets the remote sensing monitoring requirements using greenhouse gases monitoring business applications model to improve the monitoring capability of environmental protection department. Copyright© (2013) by the Asian Association on Remote Sensing.

关键词： Systems analysis

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A broadcasting multiple blind signature scheme based on quantum GHZ entanglement

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International Journal of Modern Physics: Conference Series 2014年第33期ijmpcs卷

作者： Yuan Tian Hong Chen Yan Gao Honglin Zhuang Haigang Lian Zhengping Han Peng Yu Xiangze Kong Xiaojun Wen Key Laboratory of Data Engineering and Knowledge Engineering China (Remin University of China) of Ministry of Education Beijing 100872 China School of Information Renmin University of China Beijing 100872 China China Computer User Association Information Protection Branch Beijing 100089 China School of Computer Science and Engineering Beihang University Beijing 100083 China School of Electronics & Information Engineering Shenzhen Polytechnic Shenzhen 518055 China

Using the correlation of the GHZ triplet states, a broadcasting multiple blind signature scheme is proposed. Different from classical multiple signature and current quantum signature schemes, which could only deliver either multiple signature or unconditional security, our scheme guarantees both by adopting quantum key preparation, quantum encryption algorithm and quantum entanglement. Our proposed scheme has the properties of multiple signature, blindness, non-disavowal, non-forgery and traceability. To the best of our knowledge, we are the first to propose the broadcasting multiple blind signature of quantum cryptography.

关键词： Broadcasting multiple blind signature quantum encryption algorithm quantum entanglement quantum cryptography

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Summarizing Large-Scale database Schema Using Community Detection

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Journal of Computer Science & Technology 2012年第3期27卷 515-526页

作者：王雪周烜王珊 School of Information Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China

Schema summarization on large-scale databases is a challenge. In a typical large database schema, a great proportion of the tables are closely connected through a few high degree tables. It is thus difficult to separate these tables into clusters that represent different topics. Moreover, as a schema can be very big, the schema summary needs to be structured into multiple levels, to further improve the usability. In this paper, we introduce a new schema summarization approach utilizing the techniques of community detection in social networks. Our approach contains three steps. First, we use a community detection algorithm to divide a database schema into subject groups, each representing a specific subject. Second, we cluster the subject groups into abstract domains to form a multi-level navigation structure. Third, we discover representative tables in each cluster to label the schema summary. We evaluate our approach on Freebase, a real world large-scale database. The results show that our approach can identify subject groups precisely. The generated abstract schema layers are very helpful for users to explore database.

关键词： schema summarization large scale community detection

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Fusing heterogeneous information for social image retrieval

Fusing heterogeneous information for social image retrieval

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Int. Workshops on Web-Age Information Management, WAIM 2012: 1st Int. Workshop on GDMM 2012, 2nd Int. Wireless Sensor Networks Workshop, IWSN 2012, 1st Int. Workshop on MDSP 2012, 3rd Int. Workshop on USDM 2012, 4th Int. Workshop on XMLDM 2012

作者： Li, Xirong MOE Key Lab. of Data Engineering and Knowledge Engineering Renmin University of China China

ISBN: (纸本)9783642330490

Given that millions of images are uploaded to the social web in a single day, how to effectively retrieve such increasing amounts of unstructured data becomes crucial. While current social platforms find images on the base of user-contributed tags, the tags are known to be subjective and noisy, and consequently put the effectiveness of social image retrieval into question. Different from existing work which focuses on analyzing individual sources of information such as textual and visual separately, in this paper we propose to fuse the heterogeneous information. We investigate the state of the art weighting methods within a linear fusion framework. Image retrieval experiments on a present day benchmark with 46 visual concept queries show encouraging results. Compared to the best search results obtained by a single source of information, the Uniform method and the Coordinate Ascent method obtain relative performance gain of 3.9% and 5.7% in terms of mean average precision. This work provides some practical guidelines for fusing multiple sources of information for improving social image retrieval. © 2012 Springer-Verlag.

关键词： Image enhancement

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A framework for personalized management of domain ontologies

A framework for personalized management of domain ontologies

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2012 IEEE/ACIS 11th International Conference on Computer and Information Science, ICIS 2012

作者： Liu, Runnan Wang, Puwei Zheng, Shixian Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Ministry of Education Beijing 100872 China

ISBN: (纸本)9780769546940

As the sharable and reusable domain knowledge, domain ontology increasingly serves as a foundation for semantic Web. Personalized management of domain ontologies is to provide personalized views of domain ontologies to users during run time according to user preferences. It helps that users can focus on their interested parts, instead of the whole. It increases the efficiency of ontology-based application. This paper proposes a framework for personalized management of domain ontologies. In this framework, a user model firstly is introduced to describe user preferences. Secondly, domain ontologies are decomposed into moderate-scale modules with high cohesion and low coupling. During run time, modules that a user is interested in are selected out based on the user's preferences. Finally, the selected modules are combined to construct personalized views of domain ontologies for the user. © 2012 IEEE.

关键词： Ontology

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Combining N-gram retrieval with weights propagation on massive RDF graphs

Combining N-gram retrieval with weights propagation on massi...

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2012 9th International Conference on Fuzzy Systems and knowledge Discovery, FSKD 2012

作者： Hu, He Du, Xiaoyong Key Labs of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China Beijing China

ISBN: (纸本)9781467300223

N-gram approach takes the position information into account additionally and thus can offer higher accuracy in query answering than keyword based approaches and is widely used in IR and NLP. However, in large-scale RDF graphs, URIs instead of documents are the ranking and querying units;URIs are usually much shorter than documents, and different URIs are interlinked into a massive network. One shot n-gram querying is usually not good for the RDF data in many cases. In this paper, we present a hybrid framework which combines the n-gram retrieval with link analysis based weight propagation. The idea is to exploit the link structures in the RDF data graphs and propagate the one shot n-gram score weights along with these links. Large scale experiments using MapReduce on Billion Triples Challenge dataset show the hybrid framework achieves an 80.3% improvement in relevance scores over mere n-gram retrieval. © 2012 IEEE.

关键词： MapReduce

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Extracting domain-relevant term using wikipedia based on random walk model

Extracting domain-relevant term using wikipedia based on ran...

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7th ChinaGrid Annual Conference, ChinaGrid 2012

作者： Wu, Wenjuan Liu, Tao Hu, He Du, Xiaoyong Key Labs of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China Beijing China

ISBN: (纸本)9780769548166

In this paper we present a new approach for the automatic identification of domain-relevant concepts and entities of a given domain using the category and page structures of the Wikipedia in a language independent way. By applying Markov random walk algorithm on the weighted Wikipedia link graph, our approach can identify large quantities of domain-relevant concepts and entities with very little human effort. Experimental results show that our method achieves high accuracy and acceptable efficiency in domainrelevant term extraction. © 2012 IEEE.

关键词： Markov processes

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