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International Conference on Data science and Advanced Analytics (DSAA)

作者： Danqin Wang Xiaolong Zhang Intelligent Information Processing and Real-time Industrial Systems Hubei Province Key Laboratory Wuhan China School of Computer Science and Technology Wuhan University of Science and Technology

Accompanying increasing competition among the communication industry, maintaining and improving the stability and loyalty of customers has become the key determinant of profitability. In order to prevent the loss of customers, we need to identify the stable users by data mining model. Through the evaluation of three models, Random Forest model performs with better robustness. This model can describe and predict most of the stable users in a shorter period of time. Consequently, the result will provide operators with the advantage of adopting reasonable marketing tactics timely.

关键词： Stability analysis Profitability Analytical models Prediction algorithms Logistics Accuracy

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Social sensing enhanced time estimation for bus service

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Concurrency and Computation: Practice and Experience 2015年第15期27卷

作者： Jin Liu Juan Li Xiaohui Cui Xiaoguang Niu Xiaoping Sun Jing Zhou State Key Lab. of Software Engineering Computer School Wuhan University Wuhan China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China International School of Software Wuhan University Wuhan China Computer School Wuhan University Wuhan China Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science Communication University of China China

The precise prediction of bus routes or the arrival time of buses for a traveler can enhance the quality of bus service. However, many social factors influence people's preferences for taking buses. These social factors may include heavy traffic cost, traffic congestion, poor air quality and so forth. Existing prediction techniques rarely consider social sensing when predicting the bus arrival time. Accordingly, this paper proposes a social sensing enhanced service for predicting bus routes, which integrates sensing ability and social networks to understand and measure the influence between social events and vehicle velocity. We focus on the analysis of two different attributions: PT service quality attributions PEA s and road condition attributions PRCA s. Both of them synthesize the social sensing in their evaluation of bus routes. PEA represents individual preferences and PRCA represents physical factors that significantly influence vehicle velocity. Bus relevant social events were further categorized into PEA events or PRCA events. PEA s of buses were scored according to the tendency of bus conditions reflected in social events. Furthermore, an artificial neural network prediction model is established to estimate the bus travel time. Copyright © 2015 John Wiley & Sons, Ltd.

关键词： social sensing in-time bus service bus route arrival time estimation

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Primal least squares twin support vector regression

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Journal of Zhejiang University-science C(computers and Electronics) 2013年第9期14卷 722-732页

作者： Hua-juan HUANG Shi-fei DING Zhong-zhi SHI School of Computer Science and Technology China University of Mining and Technology Key Lab of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences

The training algorithm of classical twin support vector regression (TSVR) can be attributed to the solution of a pair of quadratic programming problems (QPPs) with inequality constraints in the dual ***,this solution is affected by time and memory constraints when dealing with large *** this paper,we present a least squares version for TSVR in the primal space,termed primal least squares TSVR (PLSTSVR).By introducing the least squares method,the inequality constraints of TSVR are transformed into equality ***,we attempt to directly solve the two QPPs with equality constraints in the primal space instead of the dual space;thus,we need only to solve two systems of linear equations instead of two *** results on artificial and benchmark datasets show that PLSTSVR has comparable accuracy to TSVR but with considerably less computational *** further investigate its validity in predicting the opening price of stock.

关键词： Twin support vector regression Least squares method Primal space Stock prediction

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Corrigendum to “Fast and scalable lock methods for video coding on many-core architecture” [J. Vis. Commun. 25 (7) (2014) 1758–1762]

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Journal of Visual Communication and Image Representation 2015年 26卷 350-350页

作者： Weizhi Xu Hui Yu Dianjie Lu Fenglong Song Da Wang Xiaochun Ye Songwei Pei Dongrui Fan Hongtao Xie Institute of Microelectronics Tsinghua University Beijing China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Information Science and Engineering Shandong Normal University Jinan China Department of Computer Science and Technology Beijing University of Chemical Technology Beijing China Institute of Information Engineering Chinese Academy of Sciences National Engineering Laboratory for Information Security Technologies Beijing China

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Corrigendum to “Fast and scalable lock methods for video coding on many-core architecture” [J. Vis. Commun. Image R. 25(7) (2014) 1758–1762]

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Journal of Visual Communication and Image Representation 2015年 27卷 57-57页

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An energy efficient cluster-based routing protocol for intelligent environmental monitoring system

An energy efficient cluster-based routing protocol for intel...

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International Conference on Systems and Informatics (ICSAI)

作者： Dapeng Cheng Yingjie Song Yanyan Mao Xiangrong Wang School of Computer Science and Technology Shandong Institute of Business and Technology Yantai China College of Information Science and Engineering Shandong University of Science and Technology Qingdao China Key Laboratory of Intelligent Information Processing in Universities of Shandong (Shandong Institute of Business and Technology) Yantai china

ISBN: (纸本)9781479954599

Routing is a basic service for intelligent environmental monitoring system. However, traditional routing protocols cause unnecessary energy consumption due to the high communication overhead. In this paper, we proposed RERP, an energy efficient cluster-based routing protocol for intelligent environmental monitoring system. RERP improves LEACH protocol by limiting the selection range of cluster head. RERP also achieves reasonable cluster head election by considering residual energy, relative density and centroid distance. Simulation results show that RERP can save 54 th percentile energy more than LEACH after 2000 clustering rounds. When the network size is 500, RERP can still guarantee 99.6% nodes alive after 2000 clustering rounds.

关键词： Wireless sensor networks Artificial intelligence Clustering algorithms Nominations and elections Routing protocols Environmental monitoring

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LDDP: A location-based directed diffusion routing protocol for smart home sensor network

LDDP: A location-based directed diffusion routing protocol f...

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International Conference on Systems and Informatics (ICSAI)

ISBN: (纸本)9781479954599

Directed diffusion protocol enables data-centric routing for smart home sensor network. However, traditional directed diffusion protocol makes all nodes participating in the routing process. This causes a lot of redundant data transmission which brings unnecessary energy consumption. In this paper, we proposed LDDP, a location-based directed diffusion routing protocol for smart home sensor network, which reduces the number of nodes involved in data forwarding by room-based partitioning algorithm. Simulation results show that LDDP has better scalability than traditional DDP. LDDP can save 76 th percentile energy when the node number is 200 and the transmission times is 5000. When the network size is 250, LDDP can also brings 40kb/s network throughput gain than traditional DDP.

关键词： Smart homes Wireless sensor networks Routing protocols Routing Energy consumption Educational institutions Data communication

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Weight balancing on boundaries and Skeletons 14

Weight balancing on boundaries and Skeletons

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30th Annual Symposium on Computational Geometry, SoCG 2014

作者： Barba, Luis Cheong, Otfried De Carufel, Jean-Lou Dobbins, Michael Gene Fleischer, Rudolf Kawamura, Akitoshi Korman, Matias Okamoto, Yoshio Pach, János Tang, Yuan Tokuyama, Takeshi Verdonschot, Sander Wang, Tianhao Boursier FRIA du FNRS ULB Brussels Belgium School of Computer Science Carleton University Ottawa Canada Department of Computer Science KAIST Daejeon Korea Republic of GAIA POSTECH Pohang Korea Republic of IIPL and SCS Fudan University Shanghai China CS GUtech Muscat Oman Department of Computer Science University of Tokyo Tokyo Japan National Institute of Informatics Tokyo Japan JST ERATO Kawarabayashi Project Japan Department of Communication Engineering and Informatics University of Electro-Communications Tokyo Japan EPFL Lausanne Switzerland Rényi Institute Budapest Hungary Software School Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China Graduate School of Information Sciences Tohoku University Sendai Japan

ISBN: (纸本)9781450325943

Given a polygonal region containing a target point (which we assume is the origin), it is not hard to see that there are two points on the perimeter that are antipodal, i.e., whose midpoint is the origin. We prove three generalizations of this fact. (1) For any polygon (or any bounded closed region with connected boundary) containing the origin, it is possible to place a given set of weights on the boundary so that their barycenter (center of mass) coincides with the origin, provided that the largest weight does not exceed the sum of the other weights. (2) On the boundary of any 3-dimensional bounded polyhedron containing the origin, there exist three points that form an equilateral triangle centered at the origin. (3) On the 1-skeleton of any 3-dimensional bounded convex polyhedron containing the origin, there exist three points whose center of mass coincides with the origin. Copyright 2014 ACM.

关键词： Computational geometry

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News Credibility Evaluation on Microblog with a Hierarchical Propagation Model

News Credibility Evaluation on Microblog with a Hierarchical...

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IEEE International Conference on Data Mining (ICDM)

作者： Zhiwei Jin Juan Cao Yu-Gang Jiang Yongdong Zhang University of Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology Beijing CAS China School of Computer Science Fudan University Shanghai China

ISBN: (纸本)9781479943012

Benefiting from its openness, collaboration and real-time features, Micro blog has become one of the most important news communication media in modern society. However, it is also filled with fake news. Without verification, such information could spread promptly through social network and result in serious consequences. To evaluate news credibility on Micro blog, we propose a hierarchical propagation model. We detect sub-events within a news event to describe its detailed aspects. Thus, for a news event, a three-layer credibility network consisting of event, sub-events and messages can represent it from different scale and reveal vital information for credibility evaluation. After linking these entities with their semantic and social associations, the credibility value of each entity is propagated on this network to achieve the final evaluation result. By formulating this propagation process as a graph optimization problem, we provide a globally optimal solution with an iterative algorithm. Experiments conducted on two real-world datasets show that the proposed model boosts the accuracy by more than 6% and the F-score by more than 16% over a baseline method.

关键词： Optimization Clustering algorithms Vectors Semantics Feature extraction Symmetric matrices Media

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Active learning for protein function prediction in protein-protein interaction networks

Active learning for protein function prediction in protein-p...

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8th IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2013

作者： Xiong, Wei Xie, Luyu Guan, Jihong Zhou, Shuigeng School of Computer Science Shanghai Key Lab of Intelligent Information Processing Fudan University Shanghai China Department of Computer Science and Technology Tongji University Shanghai China

ISBN: (纸本)9783642391583

The high-throughput technologies have led to vast amounts of protein-protein interaction (PPI) data, and a number of approaches based on PPI networks have been proposed for protein function prediction. However, these approaches do not work well if annotated proteins are scarce in the networks. To address this issue, we propose an active learning based approach that uses graph-based centrality metrics to select proper candidates for labeling. We first cluster a PPI network by using the spectral clustering algorithm and select some proper candidates for labeling within each cluster, and then apply a collective classification algorithm to predict protein function based on these annotated proteins. Experiments over two real datasets demonstrate that the active learning based approach achieves better prediction performance by choosing more informative proteins for labeling. Experimental results also validate that betweenness centrality is more effective than degree centrality and closeness centrality in most cases. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Proteins

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