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4th Workshop on knowledge Discovery and data Mining Meets Linked Open data, Know@LOD 2015, co-located with 12th Extended Semantic Web Conference, ESWC 2015

作者： Ristoski, Petar Paulheim, Heiko Svátek, Vojtěch Zeman, Václav University of Mannheim Research Group Data and Web Science Germany University of Economics Department of Information and Knowledge Engineering Czech Republic

The 2015 edition of the Linked data Mining Challenge, conducted in conjunction with Know@LOD 2015, has been the third edition of this challenge. This year's dataset collected movie ratings, where the task was to classify well and badly rated movies. The solutions submitted reached an accuracy of almost 95%, which is a clear advancement over the baseline of 60%. However, there is still headroom for improvement, as the majority vote of the three best systems reaches an even higher accuracy. Copyright © 2015 for the individual papers by the papers' authors.

关键词： Linked data

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Web of data and web of entities: Identity and reference in interlinked data in the semantic web

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Philosophy and Technology 2012年第1期25卷 5-26页

作者： Bouquet, Paolo Stoermer, Heiko Vignolo, Massimiliano Department of Information Engineering and Computer Science University of Trento Trento Italy Fondazione Bruno Kessler Data Knowledge Management Unit Trento Trento Italy

Using web standards, such as uniform resource identifiers (URIs), XML and HTTP, for naming and describing resources which are not information objects is the key difference between the Web as we know it today and the Semantic Web. Naming and interlinking this type of resources by HTTP URIs (instead of individual constants in a formal language) is the key feature which distinguishes traditional knowledge representation from web-scale knowledge representation. However, this use of URIs brought back attention to the old philosophical problem of identity and reference in a new form. In this paper, we analyze the new version of the problem, provide a formal model for dealing with it when interlinking knowledge on the Web, and argue for the need of a distinction between the use of URIs for describing and accessing resources, and the use of URIs for fixing the reference. We show that in the current practice of linking data these roles are not clearly distinguished, and that this fact may cause unwanted effects and prevent some basic forms of data integration. We also discuss the role of an entity name system as a potential piece of infrastructure for fixing the reference in the Semantic Web. © 2011 Springer-Verlag.

关键词： Identity Linked data Reference Resource Semantic Web

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Myocardial Ischemia Diagnosis Using a Reduced Lead System 40

Myocardial Ischemia Diagnosis Using a Reduced Lead System

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40th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2018

作者： Aranda Hernandez, A. Bonizzi, P. Karel, J. Peeters, R. Department of Research and Technology Bakken Research Center Medtronic Maastricht Netherlands Department of Data Science and Knowledge Engineering Maastricht University Maastricht Netherlands

ISBN: (纸本)9781538636466

This research presents a novel statistical model for diagnosing acute myocardial infarction (AMI). The model is based on features extracted from a reduced lead system consisting of a subset of three leads from the standard 12-lead ECG. We selected a set of relevant parameters commonly used in the clinical practice for ECG-based AMI diagnosis, namely ST elevation and T-wave maximum. We also selectedfeatures, not used in clinical practice, that were derived from vectorcardiography and computed on the reduced three-lead system (pseudo-VCG parameters). To validate the model, we used 104 patients coming from the Physionet STAFF III database which contains 12-lead ECG recordings at baseline and in coronary artery occlusion condition during angioplasty (PTCA). Results show that pseudo-VCG features are able to diagnose AMI slightly better than ST elevation and T-wave maximum features together (area under the ROC curve (AUC) 0.87 vs AUC 0.85). When combining pseudo-VCG features together with ST elevation, and T-wave maximum, the performance improved significantly (AUC 0.95, sensitivity 89.6% and specificity 82.7%). Results indicate a potential for diagnosing AMI using the proposed reduced lead system and the selected set of features. We suggest its possible use for diagnosing AMI in long-term, ambulatory and home monitoring situations, allowing an earlier and faster diagnosis. © 2018 IEEE.

关键词： Electrocardiography Feature extraction Heart Myocardium databases Lead Standards

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Quality aware privacy protection for location-based services

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12th International Conference on database Systems for Advanced Applications, DASFAA 2007

作者： Zhen, Xiao Xiaofeng, Meng Jianliang, Xu School of Information Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering MOE Department of Computer Science Hong Kong Baptist University

ISBN: (纸本)9783540717027

Protection of users' privacy has been a central issue for location-based services (LBSs). In this paper, we classify two kinds of privacy protection requirements in LBS: location anonymity and identifier anonymity. While the location cloaking technique under the k-anonymity model can provide a good protection of users' privacy, it reduces the resolution of location information and, hence, may degrade the quality of service (QoS). To strike a balance between the location privacy and QoS, we present a quality-aware anonymity model for protecting location privacy while meeting user specified QoS requirements. In the model, a mobile user can specify the minimum anonymity level requirement upon location privacy as well as the maximum cloaking latency and the maximum cloaking region size requirements upon QoS. In accordance with the model, we develop an efficient directed-graph based cloaking algorithm to achieve both high-quality location anonymity and identifier anonymity. The performance objective is to maximize the cloaking success rate under the privacy and QoS constraints. Furthermore, we introduce an option of using dummy locations to achieve a 100% cloaking success rate at the cost of communication overhead. Experimental results show the effectiveness of our cloaking algorithm under various privacy and QoS requirements. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Tracking (position)

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Unsupervised Statistical Text Simplification

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IEEE Transactions on knowledge and data engineering 2021年第4期33卷 1802-1806页

作者： Qiang, Jipeng Wu, Xindong Department of Computer Science Yangzhou University Yangzhou Jiangsu225127 China Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education Hefei Anhui10084 China

Most recent approaches for Text Simplification (TS) have drawn on insights from machine translation to learn simplification rewrites from the monolingual parallel corpus of complex and simple sentences, yet their effectiveness strongly relies on large amounts of parallel sentences. However, there has been a serious problem haunting TS for decades, that is, the availability of parallel TS corpora is scarce or not fit for the learning task. In this paper, we will focus on one especially useful and challenging problem of unsupervised TS without a single parallel sentence. To the best of our knowledge, we present the first unsupervised text simplification system based on phrase-based machine translation system, which leverages a careful initialization of phrase tables and language models. On the widely used WikiLarge and WikiSmall benchmarks, our system respectively obtains 39.08 and 25.12 SARI points, even outperforms some supervised baselines. © 1989-2012 IEEE.

关键词： Machine translation

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Fast SimRank computation over disk-resident graphs

Fast SimRank computation over disk-resident graphs

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

作者： Zhang, Yinglong Li, Cuiping Chen, Hong Sheng, Likun Key Lab of Data Engineering and Knowledge Engineering of Ministry of Education And Department of Computer Science Renmin University of China China JiangXi Agricultural University China

ISBN: (纸本)9783642374494

There are many real-world applications based on similarity between objects, such as clustering, similarity query processing, information retrieval and recommendation systems. SimRank is a promising measure of similarity based on random surfers model. However, the computational complexity of SimRank is high and several optimization techniques have been proposed. In the paper optimization issue of Sim-Rank computation in disk-resident graphs is our primary focus. First we suggest a new approach to compute *** we propose optimization techniques that improve the time cost of the new approach from O (kN2 D2) to O (kNL), where k is the number of iteration, N is the number of nodes, L is the number of edges, and D is the average degree of nodes. Meanwhile, a threshold sieving method is presented to reduce storage and computational cost. On this basis, an external algorithm computing SimRank in disk-resident graphs is introduced. In the experiments, our algorithm outperforms its opponent whose computation complexity also is O (kNL). © Springer-Verlag 2013.

关键词： Search engines

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A fast two-stage algorithm for computing SimRank and its extensions

A fast two-stage algorithm for computing SimRank and its ext...

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1st International Workshop on Graph database, IWGD 2010, 1st International Workshop on Advanced Techniques on XML data Management, XMLDM 2010, 2nd International Workshop on WCMT 2010, Held in Conj. with WAIM 2010

作者： Jia, Xu Liu, Hongyan Zou, Li He, Jun Du, Xiaoyong Key Labs. of Data Engineering and Knowledge Engineering Ministry of Education China Department of Computer Science Renmin University of China 100872 China Department of Management Science and Engineering Tsinghua University 100084 China

ISBN: (纸本)3642167195

Similarity estimation can be used in many applications such as recommender system, cluster analysis, information retrieval and link prediction. SimRank is a famous algorithm to measure objects' similarities based on link structure. We observe that if one node has no in-link, similarity score between this node and any of the others is always zero. Based on this observation, we propose a new algorithm, fast two-stage SimRank (F2S-SimRank), which can avoid storing unnecessary zeros and can accelerate the computation without accuracy loss. Under the circumstance of no accuracy loss, this algorithm uses less computation time and occupies less main memory. Experiments conducted on real and synthetic datasets demonstrate the effectiveness and efficiency of our F2S-SimRank. © 2010 Springer-Verlag.

关键词： Cluster analysis

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Ensemble Learning Based Employment Recommendation Under Interaction Sparsity for College Students 9th

Ensemble Learning Based Employment Recommendation Under Inte...

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19th International Conference on Advanced data Mining and Applications, ADMA 2023

作者： Zhu, Haiping Zhao, Yifei Wu, Yuchen Chen, Yan Li, Wenhao Zheng, Qinghua Tian, Feng Department of Computer Science and Technology Xi’an Jiaotong University Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering Xi’an China

ISBN: (纸本)9783031466632

Recommendation systems play a crucial role in helping college students find job opportunities. However, the sparsity of interactions in employment recommendation for college students poses a challenge for models based on historical user preferences. To address this issue, we propose a novel model called Ensemble Learning based Employment Recommendation under Interaction Sparsity for College Students (EERIS). The model comprises two components: a similarity information component that uses pooled users to determine the nearest neighbor in user similarity measurement, and a global interaction component that uses interaction vectors of user groups to enhance interactions. To evaluate the missing interactions, we propose a loss function called CellLoss. These components are combined based on ensemble learning to improve the model’s generalization and scalability. Our experiments on two real-world datasets demonstrate the superior performance of the EERIS model. Ablation experiments further confirm that each component positively contributes to the model’s performance. Additionally, we design a revised metric for better model testing. Overall, the proposed EERIS model effectively addresses the interaction sparsity in employment recommendation for college students and provides satisfactory recommendations to students. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Learning systems

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A trust model for capability delegation in federated policy systems

A trust model for capability delegation in federated policy ...

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2010 International Conference on Network and Service Management, CNSM 2010

作者： Feeney, Kevin Brennan, Rob Foley, Simon N. FAME Knowledge and Data Engineering Group Trinity College Dublin Ireland FAME Department of Computer Science University College Cork Ireland

ISBN: (纸本)9781424489084

Federated policy systems are required to support the complexity and organizational heterogeneity of the modern marketplace. The Community-based Policy Management System (CBPMS) is such a distributed policy management approach. It utilizes a tree-based capability authority model to partition and delegate federated capabilities. However CBPMS delegation chains have limitations such as: performance overheads due to distributed rule evaluation, threats from malformed or malicious federated principals and a lack of flexibility with respect to delegation chain reduction or capability authority re-partitioning. In this paper we introduce a trust management model for CBPMS that addresses all of these issues. A brief security analysis is presented and a telecommunications service management use case described. © 2010 IEEE.

关键词： Chains

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Mining and predicting duplication over peer-to-peer query streams

Mining and predicting duplication over peer-to-peer query st...

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作者： Meng, Shicong Shao, Yifeng Shi, Cong Han, Dingyi Yu, Yong APEX Data and Knowledge Management Lab. Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200030 China

ISBN: (纸本)0769527027

Many previous works of data mining user queries in Peer-to-Peer systems focused their attention on the distribution of query contents. However, few has been done towards a better understanding of the time series distribution of these queries, which is vital for system performance. To remedy this situation, this paper mines query steams by using automatic time series analysis to evaluate different linear models(Box-Jenkins models and some simple windowed-mean models) for predicting the number of duplicated queries from 10 minutes to 2 hours into the future. Both the predictive power and the computational costs of these models are evaluated over 318,942,450 real world Gnutella queries collected over 3 months. We find the number of duplicated queries is consistently predictable. Simple, practical models like AR perform well on prediction. © 2006 IEEE.

关键词： Time series analysis

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