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: "a matroid framework for noncoherent random network communications"
  Abstract: Models for noncoherent error control in random linear network coding (RLNC) and store and forward (SAF) have been recently proposed. In this paper, we model different types of random network communications as the transmission of flats of matroids. This novel framework encompasses RLNC and SAF and allows us to introduce a novel protocol, referred to as random affine network coding (RANC), based on affine combinations of packets. Although the models previously proposed for RLNC and SAF only consider error control, using our framework, we first evaluate and compare the performance of different network protocols in the error-free case. We define and determine the rate, average delay, and throughput of such protocols, and we also investigate the possibilities of partial decoding before the entire message is received. We thus show that RANC outperforms RLNC in terms of data rate and throughput thanks to a more efficient encoding of messages into packets. Second, we model the possible alterations of a message by the network as an operator channel, which generalizes the channels proposed for RLNC and SAF. Error control is thus reduced to a coding-theoretic problem on flats of a matroid, where two distinct metrics can be used for error correction. We study the maximum cardinality of codes on flats in general, and codes for error correction in RANC in particular. We finally design a class of nearly optimal codes for RANC based on rank metric codes for which we propose a low-complexity decoding algorithm. The gain of RANC over RLNC is thus preserved with no additional cost in terms of complexity.

Connected through hyperedge HE-1 (induced by source paper "probability of partially solving random linear systems in network coding"):
  with members:
    - "binary systematic network coding for progressive packet decoding"
    - "constant rank codes and their connection to constant dimension codes"
    - "coding for errors and erasures in random network coding"

Connected through hyperedge HE-2 (induced by source paper "matroidal structure of skew polynomial rings with application to network coding"):
  with members:
    - "a circulant approach to skew constacyclic codes"
    - "coding for errors and erasures in random network coding"

Connected through hyperedge HE-3 (induced by source paper "probability of partially decoding network coded messages"):
  with members:
    - "constant rank codes and their connection to constant dimension codes"
    - "random linear network coding a free cipher"

Connected through hyperedge HE-4 (induced by source paper "convolutional codes in rank metric with application to random network coding"):
  with members:
    - "efficient decoding of partial unit memory codes of arbitrary rate"
    - "on partial unit memory codes based on gabidulin codes"
    - "localized dimension growth in random network coding a convolutional approach"
    - "multishot codes for network coding using rank metric codes"
    - "on network error correcting convolutional codes under the bsc edge error model"
    - "a rank metric approach to error control in random network coding"
    - "coding for errors and erasures in random network coding"

Connected through hyperedge HE-5 (induced by source paper "perfect codes in the discrete simplex"):
  with members:
    - "multiset codes for permutation channels"
    - "subset codes for packet networks"
    - "product constructions for perfect lee codes"
    - "coding for errors and erasures in random network coding"

Connected through hyperedge HE-6 (induced by source paper "multiset codes for permutation channels"):
  with members:
    - "subset codes for packet networks"
    - "coding for errors and erasures in random network coding"

Connected through hyperedge HE-7 (induced by source paper "codes on lattices for random saf routing"):
  with members:
    - "network coding with modular lattices"
    - "a new construction for constant weight codes"

Connected through hyperedge HE-8 (induced by source paper "entropy of closure operators"):
  with members:
    - "graph theoretical constructions for graph entropy and network coding based communications"

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)