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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Zheng Lin Xiaolong Jin Xueke Xu Yuanzhuo Wang Songbo Tan Xueqi Cheng CAS Key Laboratory on Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479941421

Sentiment analysis is a hard problem, while multilingual sentiment analysis is even harder due to the different expression styles in different languages. Although many methods for multilingual sentiment analysis have been developed in the open literature, most of them suffer from two major problems. The first is their excessive dependence on external tools or resources (e.g., Machine translation systems or bilingual dictionaries), which may not be readily obtained, especially for minority languages, The second is conflictive sentiments, i.e., The sentiment polarity of some parts of a text is inconsistent with its overall sentiment polarity. It is observed that in a product or service review there usually exist a few sentences which play a more important role in determining its sentiment polarity, as compared to others. Therefore, differentiating key sentences from trivial ones may be helpful to improve sentiment analysis. Inspired by this observation in this paper we propose a novel framework to estimate the sentiment polarity of reviews by virtue of opinion lexica and key sentences automatically extracted from unlabelled data. This framework cannot only overcome the problem of excessive dependence on external resources, but also is able to capture the overall sentiment polarity of reviews. Experimental results on realistic review datasets demonstrate that the proposed framework is effective and competitive with the representative baselines.

关键词： Sentiment analysis Dictionaries data mining Training Algorithm design and analysis Google Feature extraction

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ReCBuLC: Reproducing Concurrency Bugs Using Local Clocks 15

ReCBuLC: Reproducing Concurrency Bugs Using Local Clocks

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International Conference on Software Engineering (ICSE)

作者： Xiang Yuan Chenggang Wu Zhenjiang Wang Jianjun Li Pen-Chung Yew Jeff Huang Xiaobing Feng Yanyan Lan Yunji Chen Yong Guan University of Chinese Academy of Sciences Beijing China State Key Laboratory of Computer Architecture Chinese Academy of Sciences Beijing China Department of Computer Science and Engineering University of Minnesota at Twin-Cities Minneapolis USA Department of Computer Science and Engineering Texas A&M University Texas USA CAS Key Laboratory of Network Data Science and Technology Chinese Academy of Sciences Beijing China College of Information Engineering Capital Normal University Beijing China

ISBN: (纸本)9781479919345

Multi-threaded programs play an increasingly important role in current multi-core environments. Exposing concurrency bugs and debugging such multi-threaded programs have become quite challenging due to their inherent non-determinism. In order to eliminate such non-determinism, many approaches such as record-and-replay and other similar bug reproducing systems have been proposed. However, those approaches often suffer significant performance degradation because they require a large amount of recorded information and/or long analysis and replay time. In this paper, we propose an effective approach, ReCBuLC, to take advantage of the hardware clocks available on modern processors. The key idea is to reduce the recording overhead and analyzing events' global order by using time stamps recorded in each thread. Those timestamps are used to determine the global orders of shared accesses. To avoid the large overhead incurred in accessing system-wide global clock, we opt to use local per-core clocks that incur much less access overhead. We then propose techniques to resolve differences among local clocks and obtain an accurate global event order. By using per-core clocks, state-of-the-art bug reproducing systems such as PRES and CLAP can reduce the recording overheads by 1% ~ 85%, and the analysis time by 84.66% ~ 99.99%, respectively.

关键词： Clocks Program processors Computer bugs Hardware Coherence Concurrent computing Debugging

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Social evolutionary games

Social evolutionary games

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International Conference on Game Theory for networks, GameNets

作者： Jianye Yu Yuanzhuo Wang Xiao!ong Jin Xueqi Cheng CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China

In this paper, we introduce a framework of social evolutionary games (SEG) for investigating the evolution of social networks. In a SEG, a coevolutionary mechanism is adopted by agents who aim to improve his short-term utility and long-term reputation. Two examples are presented to demonstrate SEG, prisoner's dilemma game for pairwise interaction and public goods game for group interaction. Numerical simulations are performed on the two examples with different parameter settings, and the results indicates that SEG can be used as a metaphor for investigating the evolution of social networks in some scenarios.

关键词： Microscopy

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Freeway: Adaptively isolating the elephant and mice flows on different transmission paths 22

Freeway: Adaptively isolating the elephant and mice flows on...

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22nd IEEE International Conference on network Protocols, ICNP 2014

作者： Wang, Wei Sun, Yi Zheng, Kai Kaafar, Mohamed Ali Li, Dan Li, Zhongcheng Institute of Computing Technology CAS China State Key Laboratory of Networking and Switching Technology China University of Chinese Academy of Science China IBM China Research Lab China NICTA China Tsinghua University China

ISBN: (纸本)9781479962044

The network resource competition of today' data enters is extremely intense between long-lived elephant flows and latency-sensitive mice flows. Achieving both goals of high throughput and low latency respectively for the two types of flows requires compromise, which recent research has not successfully solved mainly due to the transfer of elephant and mice flows on shared links without any differentiation. However, current data enters usually adopt clos-based topology, e.g. Fat-tree/VL2, so there exist multiple shortest paths between any pair of source and destination. In this paper, we leverage on this observation to propose a flow scheduling scheme, Freeway, to adaptively partition the transmission paths into low latency paths and high throughput paths respectively for the two types of flows. An algorithm is proposed to dynamically adjust the number of the two types of paths according to the real-time traffic. And based on these separated transmission paths, we propose different flow type-specific scheduling and forwarding methods to make full utilization of the bandwidth. Our simulation results show that Freeway significantly reduces the delay of mice flow by 85.8% and achieves 9.2% higher throughput compared with Hedera. © 2014 IEEE.

关键词： Scheduling

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OpenKN: An open knowledge computational engine for network big data

OpenKN: An open knowledge computational engine for network b...

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International Conference on Advances in Social network Analysis and Mining, ASONAM

作者： Yantao Jia Yuanzhuo Wang Xueqi Cheng Xiaolong Jin Jiafeng Guo CAS Key Laboratory of Network Data Science and Technology Chinese Academy of Sciences Beijing P. R. China

With the coming of the era of big data, it is most urgent to establish the knowledge computational engine for the purpose of discovering implicit and valuable knowledge from the huge, rapidly dynamic, and complex network data. In this paper, we first survey the mainstream knowledge computational engines from four aspects and point out their deficiency. To cover these shortages, we propose the open knowledge network (OpenKN), which is a self-adaptive and evolutionable knowledge computational engine for network big data. To the best of our knowledge, this is the first work of designing the end-to-end and holistic knowledge processing pipeline in regard with the network big data. Moreover, to capture the evolutionable computing capability of OpenKN, we present the evolutionable knowledge network for knowledge representation. A case study demonstrates the effectiveness of the evolutionable computing of OpenKN.

关键词： Knowledge based systems Knowledge engineering Big data Engines Syntactics Semantics data mining

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Traffic Labeller： Collecting Internet Traffic Samples with Accurate Application Information

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China Communications 2014年第1期11卷 69-78页

作者： PENG Lizhi ZHANG Hongli YANG Bo CHEN Yuehui WU Tong School of Computer Science and Technology Harbin Institute of Technology Harbin 150002 China Provincial Key Laboratory for Network Based Intelligent Computing University of Jinan Jinan 250022 China School of Computer and Information Technology Beijing Jiaotong University Beijing 100044 China

Traffic classification research has been suffering from a trouble of collecting accurate samples with ground truth.A model named Traffic Labeller(TL) is proposed to solve this *** system captures all user socket calls and their corresponding application process information in the user mode on a Windows *** a sending data call has been captured,its 5-tuple {source IP,destination IP,source port,destination port and transport layer protocol},associated with its application information,is sent to an intermediate NDIS driver in the kernel *** the intermediate driver writes application type information on TOS field of the IP packets which match the *** this way,each IP packet sent from the Windows host carries their application ***,traffic samples collected on the network have been labelled with the accurate application information and can be used for training effective traffic classification models.

关键词： network measurement traffic cla- ssification data collection ground truth

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Account matching across heterogeneous networks

Account matching across heterogeneous networks

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International Conference on Game Theory for networks, GameNets

作者： Qiang Liu Jingyuan Li Yuanzhuo Wang Guoliang Xing Yan Ren University of Chinese Academy of Sciences Beijing China CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China National Computer Network Emergency Response Technical Team Coordination Center of China Beijing China

ISBN: (纸本)9781479979035

Due to the development of web services, many social network sites, as well as online shopping sites have been booming in the past decade, where it is a common phenomenon that people are likely to use multiple services at the same time. Discovering the correspondence between accounts of a same individual is a crucial prerequisite for many interesting cross network applications, such as improving the recommendation performance of the online shopping sites by using extra information from social network services. In this paper, we propose a gametheoretic method to identify correlation accounts of individuals between social network sites and online shopping sites with stable matching model, incorporating accounts profiles as well as historical behaviors. The results show that our method identifies up to 70% of correlation accounts between Facebook and eBay, one of the most popular social network sites and online shopping sites in the world, respectively.

关键词： Games Lead

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Freeway: Adaptively Isolating the Elephant and Mice Flows on Different Transmission Paths

Freeway: Adaptively Isolating the Elephant and Mice Flows on...

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International Conference on network Protocols

作者： Wei Wang Yi Sun Kai Zheng Mohamed Ali Kaafar Dan Li Zhongcheng Li University of Chinese Academy of Science CAS Institute of Computing Technology State Key Laboratory of Networking Switching Technology IBM China Research Lab NICTA Australia Tsinghua University

关键词： Mice Throughput Traffic control Heuristic algorithms Partitioning algorithms Topology network topology

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The 67P/Churyumov-Gerasimenko observation campaign in support of the Rosetta mission

arXiv

引用

arXiv 2017年

作者： Snodgrass, Colin A’Hearn, M.F. Aceituno, F. Afanasiev, V. Bagnulo, S. Bauer, J. Bergond, G. Besse, S. Biver, N. Bodewits, D. Boehnhardt, H. Bonev, B.P. Borisov, G. Carry, B. casanova, V. Cochran, A. Conn, B.C. Davidsson, B. Davies, J.K. de León, J. de Mooij, E. de Val-Borro, M. Delacruz, M. DiSanti, M.A. Drew, J.E. Duffard, R. Edberg, N.J.T. Faggi, S. Feaga, L. Fitzsimmons, A. Fujiwara, H. Gibb, E.L. Gillon, M. Green, S.F. Guijarro, A. Guilbert-Lepoutre, A. Gutiérrez, P.J. Hadamcik, E. Hainaut, O. Haque, S. Hedrosa, R. Hines, D. Hopp, U. Hoyo, F. Hutsemékers, D. Hyland, M. Ivanova, O. Jehin, E. Jones, G.H. Keane, J.V. Kelley, M.S.P. Kiselev, N. Kleyna, J. Kluge, M. Knight, M.M. Kokotanekova, R. Koschny, D. Kramer, E. López-Moreno, J.J. Lacerda, P. Lara, L.M. Lasue, J. Lehto, H.J. Levasseur-Regourd, A.C. Licandro, J. Lin, Z.Y. Lister, T. Lowry, S.C. Mainzer, A. Manfroid, J. Marchant, J. McKay, A.J. McNeill, A. Meech, K.J. Micheli, M. Mohammed, I. Monguió, M. Moreno, F. Muñoz, O. Mumma, M.J. Nikolov, P. Opitom, C. Ortiz, J.L. Paganini, L. Pajuelo, M. Pozuelos, F.J. Protopapa, S. Pursimo, T. Rajkumar, B. Ramanjooloo, Y. Ramos, E. Ries, C. Riffeser, A. Rosenbush, V. Rousselot, P. Ryan, E.L. Santos-Sanz, P. Schleicher, D.G. Schmidt, M. Schulz, R. Sen, A.K. Somero, A. Sota, A. Stinson, A. Sunshine, J. Thompson, A. Tozzi, G.P. Tubiana, C. Villanueva, G.L. Wang, X. Wooden, D.H. Yagi, M. Yang, B. Zaprudin, B. Zegmott, T.J. School of Physical Sciences Open University Milton KeynesMK7 6AA United Kingdom Department of Astronomy University of Maryland College ParkMD20742-2421 United States Instituto de Astrofísica de Andalucía CSIC Glorieta de la Astronomía s/n Granada18008 Spain Special Astrophysical Observatory Russian Academy of Sciences Nizhniy Arkhyz Russia Armagh Observatory College Hill ArmaghNorthern IrelandBT61 9DG United Kingdom Jet Propulsion Laboratory M/S 183-301 4800 Oak Grove Drive PasadenaCA91109 United States 04550 Spain ESA/ESAC PO Box 78 Villanueva de la Cañada28691 Spain LESIA Observatoire de Paris CNRS UPMC Univ Paris 06 Univ. Paris-Diderot 5 Place J. Janssen Meudon Pricipal Cedex92195 France Max-Planck-Institut für Sonnensystemforschung Justus-von-Liebig-Weg 3 Göttingen37077 Department of Physics American University 4400 Massachusetts Ave NW WashingtonDC20016 United States Institute of Astronomy and National Astronomical Observatory 72 Tsarigradsko Chaussée Blvd. SofiaBG-1784 Bulgaria Université Côte d’Azur OCA CNRS Lagrange France IMCCE Observatoire de Paris PSL Research University CNRS Sorbonne Universités UPMC Univ Paris 06 Univ. Lille France University of Texas Austin/McDonald Observatory 1 University Station AustinTX78712 United States Research School of Astronomy and Astrophysics Australian National University CanberraACT Australia Gemini Observatory Recinto AURA Colina El Pino s/n Casilla 603 La Serena Chile UK Astronomy Technology Centre Royal Observatory Edinburgh Blackford Hill EdinburghEH9 3HJ C/Vía Láctea s/n La Laguna38205 Spain Departamento de Astrofísica Universidad de La Laguna La Laguna Tenerife38206 Spain Astrophysics Research Centre School of Mathematics and Physics Queen’s University Belfast BT7 1NN United Kingdom Department of Astrophysical Sciences Princeton University PrincetonNJ08544 United States NASA Goddard Space Flight Center Astrochemistry Laboratory Code 691.0 GreenbeltMD20771

We present a summary of the campaign of remote observations that supported the European Space Agency’s Rosetta mission. Telescopes across the globe (and in space) followed comet 67P/Churyumov-Gerasimenko from before Rosetta’s arrival until nearly the end of mission in September 2016. These provided essential data for mission planning, large-scale context information for the coma and tails beyond the spacecraft, and a way to directly compare 67P with other comets. The observations revealed 67P to be a relatively ‘well behaved’ comet, typical of Jupiter family comets and with activity patterns that repeat from orbit-to-orbit. Comparison between this large collection of telescopic observations and the in situ results from Rosetta will allow us to better understand comet coma chemistry and structure. This work is just beginning as the mission ends – in this paper we present a summary of the ground-based observations and early results, and point to many questions that will be addressed in future studies. Copyright © 2017, The Authors. All rights reserved.

关键词： Comets

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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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