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  • Open Access


    Research on Tourist Routes Recommendation Based on the User Preference Drifting Over Time

    Chunjing Xiao1,∗, Yongwei Qiao2, Kewen Xia1, Yuxiang Zhang3

    Computer Systems Science and Engineering, Vol.33, No.2, pp. 95-103, 2018, DOI:10.32604/csse.2018.33.095

    Abstract Tourist routes recommendation is a way to improve the tourist experience and the efficiency of tourism companies. Session-based methods divide all users’ interaction histories into the same number sessions with fixed time window and treat the user preference as time sequences. There have few or even no interaction in some sessions for some users because of the high sparsity and temporal characteristics of tourist data. That lead to many session-based methods can not be applied to routes recommendation due to aggravate the sparsity. In order to better adapt and apply the characteristics of tourism data… More >

  • Open Access


    Tensor-Based User Trajectory Mining

    Chen Yu, Qinmin Hong, Dezhong Yao, Hai Jin

    Computer Systems Science and Engineering, Vol.33, No.2, pp. 87-94, 2018, DOI:10.32604/csse.2018.33.087

    Abstract The rapid expansion of GPS-embedded devices has showed the emerging new look of location-based services, enabling such offerings as travel guide services and location-based social networks. One consequence is the accumulation of a rich supply of GPS trajectories, indicating individuals’ historical position. Based on these data, we aim to mine the hot route by using a collaborative tensor calculation method. We present an efficient trajectory data processing model for mining the hot route. In this paper, we rst model the individual’s trajectory log, extract sources and destinations, use map matching to get the corresponding road More >

  • Open Access


    The Optimization Reachability Query of Large Scale Multi-Attribute Constraints Directed Graph

    Kehong Zhang, Keqiu Li

    Computer Systems Science and Engineering, Vol.33, No.2, pp. 71-85, 2018, DOI:10.32604/csse.2018.33.071

    Abstract Today, many applications such as social network and biological network develop rapidly,the graph data will be expanded constantly on a large scale. Some classic methods can not effectively solve this scale of the graph data. In the reachability query, many technologies such as N-Hop, tree, interval labels, uncertain graph processing are emerging, they also solve a lot of questions about reachability query of graph. But, these methods have not put forward the effective solution for the new issues of the multiattribute constraints reachability on directed graph. In this paper, TCRQDG algorithm effectively solves this new More >

  • Open Access


    An Iteration-Based Differentially Private Social Network Data Release

    Tianqing Zhu1, Mengmeng Yang1, Ping Xiong2, Yang Xiang1, Wanlei Zhou1

    Computer Systems Science and Engineering, Vol.33, No.2, pp. 61-69, 2018, DOI:10.32604/csse.2018.33.061

    Abstract Online social networks provide an unprecedented opportunity for researchers to analysis various social phenomena. These network data is normally represented as graphs, which contain many sensitive individual information. Publish these graph data will violate users’ privacy. Differential privacy is one of the most influential privacy models that provides a rigorous privacy guarantee for data release. However, existing works on graph data publishing cannot provide accurate results when releasing a large number of queries. In this paper, we propose a graph update method transferring the query release problem to an iteration process, in which a large More >

  • Open Access


    Preface of Special Issue on BigDataSE 2016

    Heng Qi1,2, Keqiu Li1

    Computer Systems Science and Engineering, Vol.33, No.2, pp. 57-59, 2018, DOI:10.32604/csse.2018.33.057

    Abstract This article has no abstract. More >

  • Open Access


    Rank-Order Correlation-Based Feature Vector Context Transformation for Learning to Rank for Information Retrieval

    Jen-Yuan Yeh

    Computer Systems Science and Engineering, Vol.33, No.1, pp. 41-52, 2018, DOI:10.32604/csse.2018.33.041

    Abstract As a crucial task in information retrieval, ranking defines the preferential order among the retrieved documents for a given query. Supervised learning has recently been dedicated to automatically learning ranking models by incorporating various models into one effective model. This paper proposes a novel supervised learning method, in which instances are represented as bags of contexts of features, instead of bags of features. The method applies rank-order correlations to measure the correlation relationships between features. The feature vectors of instances, i.e., the 1st-order raw feature vectors, are then mapped into the feature correlation space via More >

  • Open Access


    A Scheduling Extension Scheme of the Earliest Deadline First Policy for Hard Real-Time Uniprocessor Systems Integrated on Posix Threads Based on Linux

    Vidblain Amaro-Ortega1,∗, Arnoldo Díaz-Ramírez2, Brenda Leticia Flores-Ríos1, Félix Fernando González-Navarro1, Frank Werner3, Larysa Burtseva1

    Computer Systems Science and Engineering, Vol.33, No.1, pp. 31-40, 2018, DOI:10.32604/csse.2018.33.031

    Abstract The Linux operating system has been employed to execute numerous real-time applications. However, it is limited to support soft real-time systems by two scheduling policies: First-In-First-Out and Round Robin. For real-time systems with critical constraints, the soft real-time support and these scheduling policies are still insufficient. In this work, the Earliest Deadline First scheduling policy, which has been shown in theory to be an optimal one in uniprocessor systems, is introduced as an extension of the Linux kernel. This policy is implemented into the real-time class, without the necessity of defining an additional class. The More >

  • Open Access


    Probabliistic Analysis Of Electrocardiogram (Ecg) Heart Signal

    Amjad Gawanmeh1,3,∗, Usman Pervez2, Osman Hasan2,3

    Computer Systems Science and Engineering, Vol.33, No.1, pp. 21-29, 2018, DOI:10.32604/csse.2018.33.021

    Abstract Electrocardiography (ECG) is a heart signal wave that is recorded using medical sensors, which are normally attached to the human body by the heart. ECG waves have repetitive patterns that can be efficiently used in the diagnosis of heart problems as they carry several characteristics of heart operation. Traditionally, the analysis of ECG waves is done using informal techniques, like simulation, which is in-exhaustive and thus the analysis results may lead to ambiguities and life threatening scenarios in extreme cases. In order to overcome such problems, we propose to analyze ECG heart signals using probabilistic More >

  • Open Access


    A Dynamic Independent Component Analysis Approach To Fault Detection With New Statistics

    M. Teimoortashloo1, A. Khaki Sedigh2,*

    Computer Systems Science and Engineering, Vol.33, No.1, pp. 5-20, 2018, DOI:10.32604/csse.2018.33.005

    Abstract This paper presents a fault detection method based on Dynamic Independent Component Analysis (DICA) with new statistics. These new statistics are statistical moments and first characteristic function that surrogate the norm operator to calculate the fault detection statistics to determine the control limit of the independent components (ICs). The estimation of first characteristic function by its series is modified such that the effect of series remainder on estimation is reduced. The advantage of using first characteristic function and moments, over second characteristic function and cumulants, as fault detection statistics is also presented. It is shown More >

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