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Avoiding "big brother" anxiety with progressive self-management of ubiquitous computing services 5

Avoiding "big brother" anxiety with progressive self-managem...

5th International ICST Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2008

作者： Feeney, Kevin Lewis, Dave McGlinn, Kris O'Sullivan, Declan Holohan, Anne Knowledge and Data Engineering Group School of Computer Science and Statistics Trinity College Dublin Ireland Department of Sociology Trinity College Dublin Ireland

ISBN: (纸本)9789639799219

Despite the significant research over the last ten years, commercial ubiquitous computing environments and pervasive applications remain thin on the ground. This paper looks at the explosion in application creativity on the internet in recent years - the so-called web 2.0' - in order to identify the obstacles to application creativity in ubiquitous computing. Although technological and standardisation advances are progressively diminishing the scale of the technical problems in the domain, how to manage such applications in such a way so as to encourage user-acceptance remains an open question. It is a question that is particularly difficult due to the serious privacy concerns and the need for negotiated management of services between users due to physically embedded nature of sensor-driven applications. We describe a technical platform which is designed to allow users of ubiquitous computing environments to manage their own personal data and share it in a controlled way and describe an experimental programme to measure the relationship between users' perception of how much control they can exercise over their personal data and their acceptance of ubiquitous computing applications. Copyright © 2008 ICST.

关键词： Ubiquitous computing

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Depth-first algorithm of finding all association rules generated by a frequent itemset

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Journal of Donghua University (English Edition) 2006年第6期23卷 1-4+9页

作者： Wu, Kun Jiang, Bao-Qing Wei, Qing Institute of Data and Knowledge Engineering Henan University Kaifeng 475001 China Personnel Department Zhengzhou Institute of Aeronautical Industry Management Zhengzhou 450000 China Computer Science Department Henan University of Finance and Economics Zhengzhou 450000 China

The classical algorithm of finding association rules generated by a frequent itemset has to generate all nonempty subsets of the frequent itemset as candidate set of consequents. Xiongfei Li aimed at this and proposed an improved algorithm. The algorithm finds all consequents layer by layer, so it is breadth-first. In this paper, we propose a new algorithm Generate Rules by using Set-Enumeration Tree (GRSET) which uses the structure of Set-Enumeration Tree and depth-first method to find all consequents of the association rules one by one and get all association rules correspond to the consequents. Experiments show GRSET algorithm to be practicable and efficient.

关键词： Association rules

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Mining user interests from information sharing behaviors in social media

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17th Pacific-Asia Conference on knowledge Discovery and data Mining, PAKDD 2013

作者： Wang, Tingting Liu, Hongyan He, Jun Du, Xiaoyong Key Labs. of Data Engineering and Knowledge Engineering China School of Information Renmin University of China 100872 China Department of Management Science and Engineering Tsinghua University 100084 China

ISBN: (纸本)9783642374555

Mining user interests and preference plays an important role for many applications such as information retrieval and recommender systems. This paper intends to study how to infer interests for new users and inactive users from social media. Although some recently proposed methods can mine user interests efficiently, these works cannot make full use of relationship between users in their social network. In this paper, we propose a novel approach to infer interests of new users or inactive users based on social connections between users. A random-walk based mutual reinforcement model combining both text and link information is developed in the approach. More importantly, we compare the contribution of different social connections such as "follow", "retweet", "mention", and "comment" to interest sharing. Experiments conducted on real dataset show that our method is effective and outperforms existing algorithms, and different social connections have different impacts on mining user interests. © Springer-Verlag 2013.

关键词： Recommender systems

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Combining spatial cloaking and dummy generation for location privacy preserving

Combining spatial cloaking and dummy generation for location...

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8th International Conference on Advanced data Mining and Applications, ADMA 2012

作者： Xu, Nana Zhu, Dan Liu, Hongyan He, Jun Du, Xiaoyong Liu, Tao Key Labs. of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China China Department of Management Science and Engineering Tsinghua University China

ISBN: (纸本)9783642355264

Location privacy preserving is attracting more and more attentions with the wide use of accurate positioning devices. Two kinds of methods based on k-anonymity have been proposed for location privacy preserving. One is spatial cloaking and the other is dummy generation. However, simple cloaking may result in large cloaking region, especially when user distribution is sparse. Large cloaking region means low efficiency and high time cost. Dummy generation will also arouse great extra system cost. In this paper, we propose an approach that combines the two techniques to achieve an ideal complement. On one hand, cloaking algorithm is used to blur precise location into a region so that location privacy can be well protected. On the other hand, to those users whose cloaking region is large, generating limited number of dummies can help decrease the size of region. The effectiveness of our methods has been demonstrated by comprehensive experiments. © Springer-Verlag 2012.

关键词： Location

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VID Join： Mapping Trajectories to Points of Interest to Support Location-Based Services

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Journal of Computer science & Technology 2015年第4期30卷 725-744页

作者：商烁谢珂心郑凯刘家俊文继荣 Department of Computer Science China University of Petroleum Beijing 102249 China School of Information Technology and Electrical Engineering The University of Queensland Brisbane QLD 4072 Australia School of Computer Science and Technology Soochow University Suzhou 215006 China Commonwealth Scientific and Industrial Research Organisation Kenmore QLD 4069 Australia Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Beijing 100080 China

Variable influence duration （VID） join is a novel spatio-temporal join operation between a set T of trajectories and a set P of spatial points. Here, trajectories are traveling histories of moving objects （e.g., travelers）, and spatial points are points of interest （POIs, e.g., restaurants）. VID join returns all pairs of （τs, p） if τs is spatially close to p for a long period of time, where τs is a segment of trajectory τ ∈ T and p ∈ P. Each returned （τs, p） implies that the moving object associated with τs stayed at p （e.g., having dinner at a restaurant）. Such information is useful in many aspects, such as targeted advertising, social security, and social activity analysis. The concepts of influence and influence duration are introduced to measure the spatial closeness between τ and p, and the time spanned, respectively. Compared to the conventional spatio-temporal join, the VID join is more challenging since the join condition varies for different POIs, and the additional temporal requirement cannot be indexed effectively. To process the VID join e？ciently, three algorithms are developed and several optimization techniques are applied, including spatial duplication reuse and time duration based pruning. The performance of the developed algorithms is verified by extensive experiments on real spatial data.

关键词： trajectory spatial database spatial join spatio-temporal join

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Detecting Hot Events from Web Search Logs

Detecting Hot Events from Web Search Logs

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11th International Conference on Web-Age Information Management (WAIM 2010)

作者： Gu, Yingqin Cui, Jianwei Liu, Hongyan Jiang, Xuan He, Jun Du, Xiaoyong Li, Zhixu Key Labs. of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China Beijing 100872 China Department of Management Science and Engineering Tsinghua University Beijing 100084 China

ISBN: (纸本)9783642142451

Detecting events from web resources is a challenging task, attracting many attentions in recent years. Web search log is an important data source for event detection because the information it contains reflects users' activities and interestingness to various real world events. There are three major issues for event detection from web search logs: effectiveness, efficiency and the organization of detected events. In this paper, we develop a novel Topic and Event Detection method, TED, to address these issues. We first divide the whole data into topics for efficiency consideration, and then incorporate link information, temporal information and query content to ensure the quality of detected events. Finally, events detected are organized through the proposed interestingness measure as well as topics they belong to. Experiments are conducted on a commercial search engine log. The results demonstrate that our method can effectively and efficiently detect hot events and give a meaningful organization of them.

关键词： Event detection click-through data efficient algorithm

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Effectively grouping named entities from clickthrough data into clusters of generated keywords 16

Effectively grouping named entities from clickthrough data i...

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16th Pacific Asia Conference on Information Systems, PACIS 2012

作者： Jiang, Xuan Liu, Hongyan He, Jun Zhu, Rui Du, Xiaoyong Key Labs of Data Engineering and Knowledge Engineering MOE China School of Information Renmin University of China Beijing China Department of Management Science and Engineering Tsinghua University Beijing China

Many studies show that named entities are closely related to users' search behaviors, which brings increasing interest in studying named entities in search logs recently. This paper addresses the problem of forming fine grained semantic clusters of named entities within a broad domain such as "company", and generating keywords for each cluster, which help users to interpret the embedded semantic information in the cluster. By exploring contexts, URLs and session IDs as features of named entities, a three-phase approach proposed in this paper first disambiguates named entities according to the features. Then it properly weights the features with a novel measurement, calculates the semantic similarity between named entities with the weighted feature space, and clusters named entities accordingly. After that, keywords for the clusters are generated using a text-oriented graph ranking algorithm. Each phase of the proposed approach solves problems that are not addressed in existing works, and experimental results obtained from a real click through data demonstrate the effectiveness of the proposed approach.

关键词： Semantics

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Detecting event rumors on Sina Weibo automatically

Detecting event rumors on Sina Weibo automatically

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

作者： Sun, Shengyun Liu, Hongyan He, Jun Du, Xiaoyong Key Labs. of Data Engineering and Knowledge Engineering China School of Information Renmin University of China 100872 China Department of Management Science and Engineering Tsinghua University 100084 China

ISBN: (纸本)9783642374005

Sina Weibo has become one of the most popular social networks in China. In the meantime, it also becomes a good place to spread various spams. Unlike previous studies on detecting spams such as ads, pornographic messages and phishing, we focus on identifying event rumors (rumors about social events), which are more harmful than other kinds of spams especially in China. To detect event rumors from enormous posts, we studied the characteristics of event rumors and extracted features which can distinguish rumors from ordinary posts. The experiments conducted on real dataset show that the new features are effective to improve the rumor classifier. Further analysis of the event rumors reveals that they can be classified into 4 different types. We propose an approach for detecting one major type, text-picture unmatched event rumors. The experiment demonstrates that this approach is well-performed. © 2013 Springer-Verlag.

关键词： Social networking (online)

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A framework for specification and performance evaluation of service discovery protocols in mobile ad-hoc networks

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Ad Hoc Networks 2006年第1期4卷 1-23页

作者： Shenoi, Avinash Yesha, Yelena Yesha, Yaacov Joshi, Anupam Department of Computer Science and Electrical Engineering University of Maryland Baltimore County 1000 Hilltop Circle Baltimore MD 21250 United States Ebiquity Research Group Department of Computer Science and Electrical Engineering University of Maryland Baltimore County IEEE Transaction on Knowledge and Data Engineering IEEE ACM UMBC IEEE Transactions of Fuzzy Systems IEEE IEEE-CS ACM

Service discovery protocols are extremely important for developing distributed applications in ad-hoc environments. However to perform Service Discovery in mobile ad-hoc networks requires the design and development of extremely complex and dynamic systems. This requires a paradigm shift in the methodologies employed to design and evaluate these systems so as to ensure quality and correctness. Currently there exists no generic method for formally specifying these systems. Due to this it is extremely difficult to formally analyze protocols in this domain to study and observe the behavior. The same issue also hinders comparison of different protocols against a fixed set of metrics. In this work we propose a framework for the formal specification of service discovery protocols in mobile ad-hoc networks. The purpose of this framework is to provide a formal basis for performance evaluation and behavioral study of these protocols. This allows different service discovery architectures to be evaluated against a given set of metrics, a generic way to specify protocols and an automated process for performance evaluation and behavioral study. © 2004 Elsevier B.V. All rights reserved.

关键词： Network protocols

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Acute MI Detection Derived from ECG Parameters Distribution

Acute MI Detection Derived from ECG Parameters Distribution

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2019 Computing in Cardiology, CinC 2019

作者： Aranda, Alfonso Karel, Joël Bonizzi, Pietro Peeters, Ralf Maastricht University Department of Data Science and Knowledge Engineering Netherlands Medtronic Bakken Research Center Endepolsdomein 5 Maastricht6229GW Netherlands

ISBN: (纸本)9781728169361

Several studies in the past have evaluated the use of different ECG-based features to diagnose acute myocardial infarction (AMI). This was generally done by looking at how well a feature reflects differences between baseline (no AMI) and AMI situations. This approach tends to overlook the progress of AMI and to underestimate false positives when implemented into a continuous monitoring setting and therefore appears inadequate for it. This has hindered the adoption of those methods in the clinical practice. In this research, we present a novel set of parameters for the dynamic assessment of AMI condition. Those parameters are obtained by analyzing the changes over time in the distribution properties of ECG-based features. © 2019 Creative Commons.

关键词： Electrocardiograms

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