human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "smartphone based vehicle telematics a ten year anniversary"
  Abstract: Just like it has irrevocably reshaped social life, the fast growth of smartphone ownership is now beginning to revolutionize the driving experience and change how we think about automotive insurance, vehicle safety systems, and traffic research. This paper summarizes the first ten years of research in smartphone-based vehicle telematics, with a focus on user-friendly implementations and the challenges that arise due to the mobility of the smartphone. Notable academic and industrial projects are reviewed, and system aspects related to sensors, energy consumption, cloud computing, vehicular ad hoc networks, and human-machine interfaces are examined. Moreover, we highlight the differences between traditional and smartphonebased automotive navigation, and survey the state-of-the-art in smartphone-based transportation mode classification, driver classification, and road condition monitoring. Future advances are expected to be driven by improvements in sensor technology, evidence of the societal benefits of current implementations, and the establishment of industry standards for sensor fusion and driver assessment

Connected through hyperedge HE-1 (induced by source paper "driver identification by neural network on extracted statistical features from smartphone data"):
  with members:
    - "regularized deep networks in intelligent transportation systems a taxonomy and a case study"
    - "smartphone based driving style classification using features made by discrete wavelet transform"
    - "driver identification using automobile sensor data from a single turn"

Connected through hyperedge HE-2 (induced by source paper "mining user behaviour from smartphone data a literature review"):
  with members:
    - "inferring transportation modes from gps trajectories using a convolutional neural network"
    - "trajectorynet an embedded gps trajectory representation for point based classification using recurrent neural networks"
    - "deeptransport learning spatial temporal dependency for traffic condition forecasting"
    - "semmatch road semantics based accurate map matching for challenging positioning data"

Connected through hyperedge HE-3 (induced by source paper "socially aware congestion control in ad hoc networks current status and the way forward"):
  with members:
    - "privacy preserving schemes for ad hoc social networks a survey"
    - "socially aware networking a survey"
    - "antnet distributed stigmergetic control for communications networks"

Connected through hyperedge HE-4 (induced by source paper "a machine learning approach for smartphone based sensing of roads and driving style"):
  with members:
    - "time series classification by class specific mahalanobis distance measures"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CY(Computers and Society)