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Lecture Notes in Computer Science

作者： Wang, Qiuyue Ramírez, Georgina Marx, Maarten Theobald, Martin Kamps, Jaap School of Information Renmin University of China China Key Lab. of Data Engineering and Knowledge Engineering MOE China Universitat Pompeu Fabra Spain University of Amsterdam Netherlands Max-Planck-Institut für Informatik Germany

ISBN: (纸本)9783642357336

This paper presents an overview of the INEX 2011 data-Centric Track. Having the ad hoc search task running its second year, we introduced a new task, faceted search task, whose goal is to provide the infrastructure to investigate and evaluate different techniques and strategies of recommending facet-values to aid the user to navigate through a large set of query results and quickly identify the results of interest. The same IMDB collection as last year was used for both tasks. A total of 9 active participants contributed a total of 60 topics for both tasks and submitted 35 ad hoc search runs and 13 faceted search runs. A total of 38 ad hoc search topics were assessed, which included 18 subtopics for 13 faceted search topics. We discuss the setup for both tasks and the results obtained by their participants. © Springer-Verlag 2012.

关键词： XML

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Preventing Recommendation Attack in Trust-Based Recommender Systems

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Journal of Computer Science & Technology 2011年第5期26卷 823-828页

作者：张富国 School of Information and Technology Jiangxi University of Finance and Economics Institute of Information Resource Management Jiangxi University of Finance and Economics Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics

Despite its success,similarity-based collaborative filtering suffers from some limitations,such as scalability,sparsity and recommendation *** work has shown incorporating trust mechanism into traditional collaborative filtering recommender systems can improve these *** argue that trust-based recommender systems are facing novel recommendation attack which is different from the profile injection attacks in traditional recommender *** the best of our knowledge,there has not any prior study on recommendation attack in a trust-based recommender *** analyze the attack problem,and find that ＂victim＂ nodes play a significant role in the ***,we propose a data provenance method to trace malicious users and identify the ＂victim＂ nodes as distrust users of recommender *** study of the defend method is done with the dataset crawled from Epinions website.

关键词： data lineage ＂victim＂ node attack trust propagation

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A RFID mixed coding scheme based on huffman algorithm

A RFID mixed coding scheme based on huffman algorithm

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2011 International Conference on Management of e-Commerce and e-Government, ICMeCG 2011

作者： Jian, Jiang Guoqiong, Liao Hao, Wang Qizhi, Wan School of Information Technology Jiangxi University of Finance and Economics Nanchang China Jiangxi Key Laboratory of Data and Knowledge Engineering Nanchang Nanchang China

ISBN: (纸本)9780769545448

In RFID application systems with multiple packaging layers, labeling packaging relationship of objects in different packaging layers by encoding methods is a important technology field. Prefix-based labeling scheme is a method by which the packaging relationship of objects amounts to testing whether one object is an prefix of the other, whereas the region numbering scheme is a method by which an ancestor query amount to an interval containment test on the labels. This paper first presents a mixed-encoding scheme based on Huffman algorithm, then propose a variant of this encoding scheme in which new "virtual nodes" are involved in order to improve the stability of encoding. Our experiments prove that the mixed-based encoding scheme is effective due to the enhancement of update performance and query efficiency. © 2011 IEEE.

关键词： Encoding (symbols)

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Clustering XML search results based on content and structure similarity

Clustering XML search results based on content and structure...

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2011 International Conference on Management of e-Commerce and e-Government, ICMeCG 2011

作者： Min-Juan, Zhong Chang-Xuan, Wan De-Xi, Liu Xian-Pei, Jiao School of Information and Technology Jiangxi University of Finance and Economics Nanchang China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9780769545448

Clustering XML search results is an effective way to improve performance. However, the key problem is how to measure similarity between XML documents. In this paper, we propose a semantic similarity measure method combining content with structure, in which a variety of XML document features, including term element frequency, term inverse element frequency, semantic weight of tag label and level information of the term, are analyzed and applied for computing the similarity between XML documents. In addition, two new performance evaluation methodology, namely Cluster Ratio Relevant and Docu Ratio Relevant, for clustering quality are introduced motivated by the observations of relevant documents distribution and the fact that collection has no classification information. Experiment results show that proposed similarity method(CAS measure)outperforms traditional document clustering(CO measure) in Cluster Ratio Relevant and Docu Ratio Relevant and produces better clustering quality. © 2011 IEEE.

关键词： XML

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A query-oriented summarization system for XML elements

A query-oriented summarization system for XML elements

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2011 International Conference on Management of e-Commerce and e-Government, ICMeCG 2011

作者： Liu, Dexi Wu, Shihan Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang 330013 China Songjiang Branch Shanghai Rural Commercial Bank Shanghai 201600 China

ISBN: (纸本)9780769545448

In document-center XML dataset, an element may contain so many text that users have to spend enough time to judge the elements returned by XML search engine are valuable or not. Query-orient XML summarization system aim to provide users a brief and readable substitution of the original retrieved elements according to the user's query, which can relieve user's reading burden effectively. In this work, we extract sentences from the results of XML search engine, and combine them as a summary. Experiments on the IEEE-CS datasets used in INEX show that, the query-oriented XML summary generated by our method is reasonable. © 2011 IEEE.

关键词： XML

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Selection of multimedia data source based on user feedback

Selection of multimedia data source based on user feedback

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2011 International Conference on Management of e-Commerce and e-Government, ICMeCG 2011

作者： Deng, Song Wan, Changxuan Liu, Xiping School of Information Technology Jiangxi University of Finance and Ecomomics Nanchang China School of Software Jiangxi Agricultural University Nanchang China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9780769545448

There are hundreds or thousands of web data sources providing data of relevance to a particular domain on the Web, so how to find a suitable set of sources quickly to integrate from a number of sources is becoming more and more important. Traditional data sources selection methods that are based on data quality do not consider quality characteristics of data sources under the different domains, but select the same quality dimensions for quality evaluation models. As a result, accuracies of a traditional method under different domains are quite different. In light of this, we propose a Web multimedia source selection method based on user feedback. We gain accurate core quality dimensions of data sources under the multimedia domain based on user feedback, and then achieve a quality estimation model of the multimedia data sources. The experiments on hundreds of real-world multimedia data sources have proved that our approach is efficient and accurate. © 2011 IEEE.

关键词： Accuracy Computers data Source data models databases Equations Mathematical model Multimedia Multimedia communication Quality Dimensions User Feedback Web data source data quality estimation model quality evaluation model quality multimedia computing mult

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Analysis of bandwagon and average hybrid attack model against trust-based recommender systems

Analysis of bandwagon and average hybrid attack model agains...

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2011 International Conference on Management of e-Commerce and e-Government, ICMeCG 2011

作者： Zhang, Fuguo School of Information and Technology Jiangxi University of Finance and Economics Nanchang China Institute of Information Resource Management Jiangxi University of Finance and Economics Nanchang China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9780769545448

Recommender systems have been accepted as a vital application on the web by offering product advice or information that users might be interested in. Despite its success, similarity-based collaborative filtering suffers from some significant limitations, such as scalability, sparsity and recommendation attack. Prior work has shown incorporating trust mechanism into traditional collaborative filtering recommender systems can improve these limitations. However, trust-based recommender systems are also known to be vulnerable to profile infection attacks. Malicious users can inject a large number of biased profiles into such a system in order to make recommendations that favor or disfavor given items. In this paper, we propose a bandwagon and average hybrid attack model and analysis the effectiveness of the attack model against topic-level trust-based recommender algorithm. The results of our experiments conducted on well-known dataset show that the hybrid attack model is more effective than other attack models. © 2011 IEEE.

关键词： Recommender systems

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A practice probability frequent pattern mining method over transactional uncertain data streams

A practice probability frequent pattern mining method over t...

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Lecture Notes in Computer Science

作者： Liao, Guoqiong Wu, Linqing Wan, Changxuan Xiong, Naixue School of Information Technology Jiangxi University of Finance and Economics Nanchang 330013 China Jiangxi Key Laboratory of Data and Knowledge Engineering Nanchang 330013 China Department of Computer Science Georgia State University United States

ISBN: (纸本)9783642236402

In recent years, large amounts of uncertain data are emerged with the widespread employment of the new technologies, such as wireless sensor networks, RFID and privacy protection. According to the features of the uncertain data streams such as incomplete, full of noisy, non-uniform and mutable, this paper presents a probability frequent pattern tree called PFP-tree and a method called PFP-growth, to mine probability frequent patterns based on probability damped windows. The main characteristics of the suggested method include: (1) adopting time-based probability damped window model to enhance the accuracy of mined frequent patterns;(2) setting an item index table and a transaction index table to speed up retrieval on the PFP-tree;and (3) pruning the tree to remove the items that cannot become frequent patterns;. The experimental results demonstrate that PFP-growth method has better performance than the main existing schemes in terms of accuracy, processing time and storage space. © 2011 Springer-Verlag.

关键词： Probability

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基于主题语义的非合作结构化Top-N深网数据源选择

基于主题语义的非合作结构化Top-N深网数据源选择

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第29届中国数据库学术会议

作者： Deng Song 邓松 Wan Changxuan 万常选 Liu Xiping 刘喜平 Jiang Tengjiao 江腾蛟 Lei Gang 雷刚 School of Information and Technology Jiangxi University of Finance and Economics Nanchang 330013 江西财经大学信息管理学院南昌 330013 Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economic 江西财经大学数据与知识工程江西省高校重点实验室南昌 330013

高效且准确地找出存在于深网中的与用户查询意图最相关的Top-N元组，是深网数据集成中的关键问题。针对数据源内容概括未见成果的现状，本文提出了一种能够有效概括非数字、非离散属性特征的非合作结构化深网数据源摘要构建方法。利用... 详细信息

高效且准确地找出存在于深网中的与用户查询意图最相关的Top-N元组，是深网数据集成中的关键问题。针对数据源内容概括未见成果的现状，本文提出了一种能够有效概括非数字、非离散属性特征的非合作结构化深网数据源摘要构建方法。利用主题词抽样，依据主题语义选择与主题词相关的特征词，通过主题词及特征词构建数据源语义摘要。实验结果表明与传统的基于词频的方法相比较，该方法在召回率及准确度方面均有较大幅度的提升。

关键词：深网数据集成检索系统优化设计信息提取主题语义

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K-nearest neighbors in uncertain graph

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2011年第10期48卷 1850-1858页

作者： Zhang, Yinglong Li, Cuiping Chen, Hong Du, Lingxia Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Ministry of Education Beijing 100872 China School of Computer and Information Engineer Jiangxi Agriculture University Nanchang 330045 China

In many areas, a lot of data have been modeled by graphs which are subject to uncertainties, such as molecular compounds and protein interaction networks. While many real applications, for example, collaborative filtering, fraud detection, and link prediction in social networks etc, rely on efficiently answering k-nearest neighbor queries (kNN), which is the problem of computing the most "similar" k nodes to a given query node. To solve the problem, in this paper a novel method based on measurement of SimRank is proposed. However, because graphs evolve over time and are uncertainly, the computing cost can be very high in practice to solve the problem using the existing algorithms of SimRank. So the paper presents an optimization algorithm. Introducing path threshold, which is suitable in both determined graph and uncertain graph, the algorithm merely considers the local neighborhood of a given query node instead of whole graph to prune the search space. To further improving efficiency, the algorithm adopts sample technology in uncertain graph. At the same time, theory and experiments interpret and verify that the optimization algorithm is efficient and effective.

关键词： Collaborative filtering

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