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Iranian Conference on Electrical Engineering (ICEE)

作者： Ayoub Bagheri Mohamad Saraee Franciska de Jong Intelligent Database Data Mining and Bioinformatics Laboratory Electrical and Computer Engineering Department Isfahan University of Technology Isfahan Iran School of Computing Science and Engineering University of Salford Manchester UK Human Media Interaction University of Twente Enschede Netherlands

With the enormous growth of online reviews in Internet, sentiment analysis has received more and more attention in information retrieval and natural language processing community. Up to now there are very few researches conducted on sentiment analysis for Persian documents. This paper considers the problem of sentiment classification for online customer reviews in Persian language. One of the challenges of Persian language is using of a wide variety of declensional suffixes. Another common problem of Persian text is word spacing. In Persian in addition to white space as interwords space, an intra-word space called pseudo-space separates word's part. One more noticeable challenge in customer reviews in Persian language is that of utilizing many informal or colloquial words in text. In this paper we study these challenges by proposing a model for sentiment classification of Persian review documents. The proposed model is based on a lemmatization approach for Persian language and is employed Naive Bayes learning algorithm for classification. Additionally we present a new feature selection method based on the mutual information method to extract the best feature collection from the initial extracted features. Finally we evaluate the performance of the model on a manually gathered collection of cellphone reviews, where the results show the effectiveness of the proposed model.

关键词： Feature extraction Mathematical model Classification algorithms Equations Mutual information Training data mining

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A Generic Construction of Proxy Signatures from Certificateless Signatures

A Generic Construction of Proxy Signatures from Certificatel...

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International Conference on Advanced Information Networking and Applications (AINA)

作者： Lei Zhang Qianhong Wu Bo Qin Josep Domingo-Ferrer Peng Zeng Jianwei Liu Ruiying Du Shanghai Key Laboratory of Trustworthy Computing Software Engineering Institute East China Normal University Shanghai China UNESCO Chair in Data Privacy Department of Computer Engineering and Mathematics Universitat Rovira i Virgili Tarragona Spain Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Computer Wuhan University China Department of Maths School of Science Xi'an University of Technology China School of Electronic and Information Engineering Beijing University of Aeronautics and Astronautics China

The primitive of proxy signatures allows the original signer to delegate proxy signers to sign on messages on behalf of the original signer. It has found numerous applications in distributed computing scenarios where delegation of signing rights is common. Certificate less public key cryptography eliminates the complicated certificates in traditional public key cryptosystems without suffering from the key escrow problem in identity-based public key cryptography. In this paper, we reveal the relationship between the two important primitives of proxy signatures and certificate less signatures and present a generic conversion from the latter to the former. Following the generic transformation, we propose an efficient proxy signature scheme with a recent certificate less signature scheme.

关键词： Artificial intelligence Bismuth Games Public key cryptography Educational institutions

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Efficient approximation of the maximal preference scores by lightweight cubic views

Efficient approximation of the maximal preference scores by ...

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15th International Conference on Extending database Technology, EDBT 2012

作者： Chen, Yueguo Cui, Bin Du, Xiaoyong Tung, Anthony K. H. Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE China Department of Computer Science Peking University Beijing China School of Information Renmin University of China Beijing China School of Computing National University of Singapore Singapore Singapore

ISBN: (纸本)9781450307901

Given a multi-features data set, a best preference query (BPQ) computes the maximal preference score (MPS) that the tuples in the data set can achieve with respect to a preference function. BPQs are very useful in applications where users want to efficiently check whether many individual data sets contain tuples that are of interest to them. Although a BPQ can be naïvely answered by issuing a top-1 query and computing the score from the returned tuple, doing so might require to load a larger number of tuples externally. In this paper, we address the problem of efficient processing BPQs by using lightweight cubic (3-dimensional) views. With these in-memory views, the MPSs of BPQs can be efficiently estimated with an error bound guaranteed, by paying only a small number of I/Os. Extensive experimental results over real-life data sets show that our approximate solution can achieve the efficiency of up to three orders of magnitude compared to exact solutions, with certain accuracy guaranteed. © 2012 ACM.

关键词： best preference score materialized views preference query top-k query

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Categorization of computing education resources with utilization of crowdsourcing 12

Categorization of computing education resources with utiliza...

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12th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL '12

作者： Chen, Yinlin Bogen II, Paul Logasa Hsieh, Haowei Fox, Edward A. Cassel, Lillian N. Department of Computer Science Virginia Tech. Blacksburg VA United States Intelligent Computing Research Team Computational Data Analytics Group Oak Ridge National Laboratory Oak Ridge TN 37931 United States School of Library and Information Science University of Iowa Iowa City IA 52242 United States Department of Computing Sciences Villanova University Villanova PA 19085 United States

ISBN: (纸本)9781450311540

The Ensemble Portal harvests resources from multiple heterogeneous federated collections. Managing these dynamically increasing collections requires an automatic mechanism to categorize records in to corresponding topics. We propose an approach to use existing ACM DL metadata to build classifiers for harvested resources in the Ensemble project. We also present our experience with utilizing the Amazon Mechanical Turk platform to build ground truth training data sets from Ensemble collections. © 2012 ACM.

关键词： Digital libraries

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Practical privacy for value-added applications in vehicular ad hoc networks 5th

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5th International Conference on Internet and Distributed computing Systems, IDCS 2012

作者： Zhang, Lei Wu, Qianhong Qin, Bo Domingo-Ferrer, Josep Shanghai Key Laboratory of Trustworthy Computing Software Engineering Institute East China Normal University Shanghai China UNESCO Chair in Data Privacy Dept. of Comp. Eng. and Maths Universitat Rovira i Virgili TarragonaCatalonia Spain Key Lab. of Aerospace Information Security and Trusted Computing Ministry of Education Wuhan University School of Computer China Department of Maths School of Science Xi’an University of Technology China

ISBN: (纸本)9783642348822

Advances in mobile networking and information processing technologies have triggered vehicular ad hoc networks (VANETs) for traffic safety and value-added applications. Most efforts have been made to address the security concerns while little work has been done to investigate security and privacy for value-added applications in VANETs. To fill this gap, we propose a value-added application, specifically, a security and privacy preserving location-based service (LBS) scheme for VANETs. For each LBS transaction, the scheme provides authentication, integrity and non-repudiation for both the service provider and the user. A user can obtain the service in an anonymous way and hence user privacy is well protected. However, a tracing procedure can be invoked to find malicious users, thereby efficiently preventing users from abusing the anonymity provided by the system. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Location based services

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Single attribute Join Queries within latest sampling periods in sensor networks

Single attribute Join Queries within latest sampling periods...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Shangfeng Mo Hong Chen Yinglong Li School of Math and Computing Science Hunan University of Science and Technology Xiangtan China Key Laboratory of Data Engineering and Knowledge Engineering of MOE School of Information Renmin University of China Beijing China

Join processing in wireless sensor networks is a challenging problem. Current solutions are not involved in the join operation among tuples of the latest sampling periods. In this article, we proposed a continuous Single attribute Join Queries within latest sampling Periods (SJQP) for wireless sensor networks. The main idea of our filter-based framework is to discard non-matching tuples, and our scheme can guarantee the result is correct independent of the filters. Experiments based on real-world sensor data show that our method performs close to a theoretical optimum and consistently outperforms the centralized join algorithm.

关键词： Base stations Wireless sensor networks Probes Filtering algorithms Temperature sensors Information filters

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Corrigendum: “Provably-secure electronic cash based on certicateless partially-blind signatures”

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Electronic Commerce Research and Applications 2013年第1期12卷 60-60页

作者： Lei Zhang Futai Zhang Bo Qin Shubo Liu East China Normal University Software Engineering Institute Shanghai Key Laboratory of Trustworthy Computing Shanghai China Universitat Rovira i Virgili Department of Computer Engineering and Mathematics UNESCO Chair in Data Privacy Tarragona Catalonia Spain Nanjing Normal University School of Computer Science and Technology China Xi’an University of Technology School of Science Department of Maths China Wuhan University School of Computer Science Wuhan China

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Context-specific miRNA regulation network predicts cancer prognosis

Context-specific miRNA regulation network predicts cancer pr...

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IEEE International Conference on Systems Biology

作者： Xionghui Zhou Juan Liu Changning Liu Simon Rayner Fengji Liang Jingfang Ju Yinghui Li Shanguang Chen Jianghui Xiong School of Computer Science Wuhan University Wuhan China Bioinformatics Research Group Key Laboratory of Intelligent Information Processing Advanced Computing Research Laboratory Institute of Computing Technology Chinese Academy of Sciences (CAS) Beijing China Bioinformatics Group State Key Laboratory of Virology Wuhan Institute of Virology Chinese Academy of Sciences (CAS) Wuhan China Bioinformatics Group and Data Coordination Center State Key Laboratory of Space Medicine Fundamentals and Application China Astronaut Research and Training Center Beijing China Department of Pathology Stony Brook University Medical Center New York USA

MicroRNAs can regulate hundreds of target genes and play a pivotal role in a broad range of biological process. However, relatively little is known about how these highly connected miRNAs-target networks are remodelled in the context of various diseases. Here we examine the dynamic alteration of context-specific miRNA regulation to determine whether modified microRNAs regulation on specific biological processes is a useful information source for predicting cancer prognosis. A new concept, Context-specific miRNA activity (CoMi activity) is introduced to describe the statistical difference between the expression level of a miRNA's target genes and non-targets genes within a given gene set (context).

关键词： Breast cancer Context Correlation Biological processes Metastasis Tumors

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Strong Security Enabled Certificateless Aggregate Signatures Applicable to Mobile Computation

Strong Security Enabled Certificateless Aggregate Signatures...

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International Conference on intelligent Networking and Collaborative Systems (INCOS)

作者： Hu Xiong Qianhong Wu Zhong Chen Key Laboratory of Network and Software Security Assurance of the Ministry of Education Institute of Software School of Electronics Engineering and Computer Science Peking University Beijing China Department of Computer Engineering and Mathematics UNESCO Chair in Data Pr Universitat Rovira i Virgili Tarragona Spain Key Laboratory of AeroSpace Information Security and Trusted Computing Ministry of Education School of Computer Wuhan University of China China

An aggregate signature scheme allows a public algorithm to aggregate n signatures of n distinct messages from n signers into a single signature. By validating the single resulting signature, one can be convinced that the messages have been endorsed by all the signers. Certificateless aggregate signatures allow the signers to authenticate messages without suffering from the complex certificate management in the traditional public key cryptography or the key escrow problem in identity-based cryptography. In this paper, we present a new efficient certificate less aggregate signature scheme. Compared with up-to-date certificate less aggregate signatures, our scheme is equipped with a number of attracting features: (1) it is shown to be secure under the standard computational Diffie-Hellman assumption in the random oracle model, (2) the security is proven in the strongest security model so far, (3) the signers do not need to be synchronized, and (4) its performance is comparable to the most efficient up-to-date schemes. These features are desirable in a mobile networking and computing environment where the storage/computation capacity of the end devices are limited, and due to the wireless connection and distributed feature, the computing devices are easy to be attacked and hard to be synchronized.

关键词： Aggregates Games Generators Synchronization Public key cryptography

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Proximity user identification using correlogram

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作者： Shahidi, Shervin Mazrooei, Parisa Esfahani, Navid Nasr Saraee, Mohammad Intelligent Databases Data Mining and Bioinformatics Research Laboratory Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156-83111 Iran Isfahan Mathematics House Isfahan 81645-356 Iran School of Computing Science and Engineering University of Salford Greater Manchester United Kingdom

ISBN: (纸本)3642163262

This paper represents a technique, applying user action patterns in order to distinguish between users and identify them. In this method, users' actions sequences are mapped to numerical sequences and each user's profile is generated using autocorrelation values. Next, cross-correlation is used to compare user profiles with a test data. To evaluate our proposed method, a dataset known as Greenberg's dataset is used. The presented approach is succeeded to detect the correct user with as high as 82.3% accuracy over a set of 52 users. In comparison to the existing methods based on Hidden Markov Model or Neural Networks, our method needs less computation time and space. In addition, it has the ability of getting updated iteratively which is a main factor to facilitate transferability. © 2010 IFIP.

关键词： Pattern recognition

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