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: "overlapped chunked network coding"
  Abstract: Network coding is known to improve the throughput and the resilience to losses in most network scenarios. In a practical network scenario, however, the accurate modeling of the traffic is often too complex and/or infeasible. The goal is thus to design codes that perform close to the capacity of any network (with arbitrary traffic) efficiently. In this context, random linear network codes are known to be capacity-achieving while requiring a decoding complexity quadratic in the message length. Chunked Codes (CC) were proposed by Maymounkov et al. to improve the computational efficiency of random codes by partitioning the message into a number of non-overlapping chunks. CC can also be capacity-achieving but have a lower encoding/decoding complexity at the expense of slower convergence to the capacity. In this paper, we propose and analyze a generalized version of CC called Overlapped Chunked Codes (OCC) in which chunks are allowed to overlap. Our theoretical analysis and simulation results show that compared to CC, OCC can achieve the capacity with a faster speed while maintaining almost the same advantage in computational efficiency.

Connected through hyperedge HE-1 (induced by source paper "the benefit of limited feedback to generation based random linear network coding in wireless broadcast"):
  with members:
    - "round robin streaming with generations"
    - "speeding multicast by acknowledgment reduction technique smart"
    - "sparse network coding with overlapping classes"

Connected through hyperedge HE-2 (induced by source paper "batched sparse codes"):
  with members:
    - "overhead optimized gamma network codes"
    - "effects of the generation size and overlap on throughput and complexity in randomized linear network coding"
    - "on the capacity of non coherent network coding"
    - "coding for linear operator channels over finite fields"
    - "communication over finite field matrix channels"
    - "sparse network coding with overlapping classes"
    - "compute and forward harnessing interference through structured codes"
    - "packing and covering properties of subspace codes for error control in random linear network coding"

Connected through hyperedge HE-3 (induced by source paper "expander chunked codes"):
  with members:
    - "batched sparse codes"
    - "overhead optimized gamma network codes"
    - "linear complexity overhead optimized random linear network codes"
    - "effects of the generation size and overlap on throughput and complexity in randomized linear network coding"
    - "throughput and latency in finite buffer line networks"
    - "sparse network coding with overlapping classes"
    - "packing and covering properties of subspace codes for error control in random linear network coding"
    - "coding schemes for line networks"

Connected through hyperedge HE-4 (induced by source paper "coding delay analysis of dense and chunked network codes over line networks"):
  with members:
    - "how fast can dense codes achieve the min cut capacity of line networks"
    - "analysis of overlapped chunked codes with small chunks over line networks"
    - "on the delay of network coding over line networks"
    - "sparse network coding with overlapping classes"

Connected through hyperedge HE-5 (induced by source paper "efficient feedback based scheduling policies for chunked network codes over networks with loss and delay"):
  with members:
    - "sparse network coding with overlapping classes"

Connected through hyperedge HE-6 (induced by source paper "analysis of overlapped chunked codes with small chunks over line networks"):
  with members:
    - "network codes with overlapping chunks over line networks a case for linear time codes"
    - "effects of the generation size and overlap on throughput and complexity in randomized linear network coding"
    - "sparse network coding with overlapping classes"
    - "coding schemes for line networks"

Connected through hyperedge HE-7 (induced by source paper "effects of the generation size and overlap on throughput and complexity in randomized linear network coding"):
  with members:
    - "sparse network coding with overlapping classes"

Connected through hyperedge HE-8 (induced by source paper "collecting coded coupons over overlapping generations"):
  with members:
    - "collecting coded coupons over generations"
    - "sparse network coding with overlapping classes"

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.IT(Information Theory)