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: "map a crowd sensing system for automatic map semantics identification"
  Abstract: Digital maps have become a part of our daily life with a number of commercial and free map services. These services have still a huge potential for enhancement with rich semantic information to support a large class of mapping applications. In this paper, we present Map++, a system that leverages standard cell-phone sensors in a crowdsensing approach to automatically enrich digital maps with different road semantics like tunnels, bumps, bridges, footbridges, crosswalks, road capacity, among others. Our analysis shows that cell-phones sensors with humans in vehicles or walking get affected by the different road features, which can be mined to extend the features of both free and commercial mapping services. We present the design and implementation of Map++ and evaluate it in a large city. Our evaluation shows that we can detect the different semantics accurately with at most 3% false positive rate and 6% false negative rate for both vehicle and pedestrian-based features. Moreover, we show that Map++ has a small energy footprint on the cell-phones, highlighting its promise as a ubiquitous digital maps enriching service.

Connected through hyperedge HE-1 (induced by source paper "coltrane convolutional trajectory network for deep map inference"):
  with members:
    - "a comparative review of recent kinect based action recognition algorithms"
    - "cnn based action recognition and supervised domain adaptation on 3d body skeletons via kernel feature maps"
    - "road network fusion for incremental map updates"
    - "riobusdata outlier detection in bus routes of rio de janeiro"
    - "tensor representations via kernel linearization for action recognition from 3d skeletons"
    - "a comparison and evaluation of map construction algorithms using vehicle tracking data"
    - "adam a method for stochastic optimization"
    - "very deep convolutional networks for large scale image recognition"

Connected through hyperedge HE-2 (induced by source paper "crescendo an infrastructure free ubiquitous cellular network based localization system"):
  with members:
    - "the diversity and scale matter ubiquitous transportation mode detection using single cell tower information"
    - "semmatch road semantics based accurate map matching for challenging positioning data"
    - "lanequest an accurate and energy efficient lane detection system"
    - "dejavu an accurate energy efficient outdoor localization system"
    - "cellsense an accurate energy efficient gsm positioning system"

Connected through hyperedge HE-3 (induced by source paper "hapi a robust pseudo 3d calibration free wifi based indoor localization system"):
  with members:
    - "a scalable deep neural network architecture for multi building and multi floor indoor localization based on wi fi fingerprinting"
    - "vifi virtual fingerprinting wifi based indoor positioning via multi wall multi floor propagation model"
    - "csi based fingerprinting for indoor localization a deep learning approach"
    - "selective ap sequence based indoor localization without site survey"
    - "a robust zero calibration rf based localization system for realistic environments"
    - "lanequest an accurate and energy efficient lane detection system"
    - "an analysis of device free and device based wifi localization systems"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-4 (induced by source paper "transitlabel a crowd sensing system for automatic labeling of transit stations semantics"):
  with members:
    - "a robust zero calibration rf based localization system for realistic environments"
    - "the diversity and scale matter ubiquitous transportation mode detection using single cell tower information"
    - "ubibreathe a ubiquitous non invasive wifi based breathing estimator"
    - "it s the human that matters accurate user orientation estimation for mobile computing applications"
    - "dejavu an accurate energy efficient outdoor localization system"
    - "crowdinside automatic construction of indoor floorplans"
    - "a hidden markov model for localization using low end gsm cell phones"

Connected through hyperedge HE-5 (induced by source paper "a robust zero calibration rf based localization system for realistic environments"):
  with members:
    - "transitlabel a crowd sensing system for automatic labeling of transit stations semantics"
    - "lanequest an accurate and energy efficient lane detection system"
    - "it s the human that matters accurate user orientation estimation for mobile computing applications"
    - "dejavu an accurate energy efficient outdoor localization system"
    - "crowdinside automatic construction of indoor floorplans"
    - "a hidden markov model for localization using low end gsm cell phones"

Connected through hyperedge HE-6 (induced by source paper "semmatch road semantics based accurate map matching for challenging positioning data"):
  with members:
    - "lanequest an accurate and energy efficient lane detection system"
    - "it s the human that matters accurate user orientation estimation for mobile computing applications"
    - "dejavu an accurate energy efficient outdoor localization system"
    - "cellsense an accurate energy efficient gsm positioning system"
    - "cellsense a probabilistic rssi based gsm positioning system"
    - "gac energy efficient hybrid gps accelerometer compass gsm localization"
    - "a hidden markov model for localization using low end gsm cell phones"
    - "on line viterbi algorithm for analysis of long biological sequences"

Connected through hyperedge HE-7 (induced by source paper "lanequest an accurate and energy efficient lane detection system"):
  with members:
    - "it s the human that matters accurate user orientation estimation for mobile computing applications"
    - "dejavu an accurate energy efficient outdoor localization system"
    - "cellsense an accurate energy efficient gsm positioning system"
    - "cellsense a probabilistic rssi based gsm positioning system"
    - "a hidden markov model for localization using low end gsm cell phones"
    - "markov localization for mobile robots in dynamic environments"

Connected through hyperedge HE-8 (induced by source paper "the diversity and scale matter ubiquitous transportation mode detection using single cell tower information"):
  with members:
    - "dejavu an accurate energy efficient outdoor localization system"
    - "cellsense an accurate energy efficient gsm positioning system"
    - "cellsense a probabilistic rssi based gsm positioning system"
    - "gac energy efficient hybrid gps accelerometer compass gsm localization"
    - "a hidden markov model for localization using low end gsm cell phones"

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)