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: "sum networks from undirected graphs construction and capacity analysis"
  Abstract: We consider a directed acyclic network with multiple sources and multiple terminals where each terminal is interested in decoding the sum of independent sources generated at the source nodes. We describe a procedure whereby a simple undirected graph can be used to construct such a sum-network and demonstrate an upper bound on its computation rate. Furthermore, we show sufficient conditions for the construction of a linear network code that achieves this upper bound. Our procedure allows us to construct sum-networks that have any arbitrary computation rate $\frac{p}{q}$ (where $p,q$ are non-negative integers). Our work significantly generalizes a previous approach for constructing sum-networks with arbitrary capacities. Specifically, we answer an open question in prior work by demonstrating sum-networks with significantly fewer number of sources and terminals.

Connected through hyperedge HE-1 (induced by source paper "sum networks from incidence structures construction and capacity analysis"):
  with members:
    - "low subpacketization schemes for coded caching"
    - "coded caching with low subpacketization levels"
    - "coded caching for networks with the resolvability property"
    - "capacity of sum networks for different message alphabets"
    - "upper bound on function computation in directed acyclic networks"
    - "fractional repetition codes with flexible repair from combinatorial designs"
    - "on the multiple unicast capacity of 3 source 3 terminal directed acyclic networks"
    - "on network coding for sum networks"

Connected through hyperedge HE-2 (induced by source paper "on computation rates for arithmetic sum"):
  with members:
    - "capacity of sum networks for different message alphabets"
    - "upper bound on function computation in directed acyclic networks"
    - "on network coding for sum networks"
    - "network coding for computing cut set bounds"
    - "optimal function computation in directed and undirected graphs"
    - "communicating the sum of sources over a network"

Connected through hyperedge HE-3 (induced by source paper "sum networks dependency on characteristic of the finite field under linear network coding"):
  with members:
    - "on achievability of an r l fractional linear network code"
    - "on network coding for sum networks"
    - "communicating the sum of sources over a network"
    - "some results on communicating the sum of sources over a network"

Connected through hyperedge HE-4 (induced by source paper "graph codes for distributed instant message collection in an arbitrary noisy broadcast network"):
  with members:
    - "energy efficient distributed coding for data collection in a noisy sparse network"
    - "computing linear transformations with unreliable components"
    - "update efficiency and local repairability limits for capacity approaching codes"
    - "computation over gaussian networks with orthogonal components"
    - "computing linear functions by linear coding over networks"
    - "network coding for computing cut set bounds"
    - "towards a queueing based framework for in network function computation"
    - "optimal function computation in directed and undirected graphs"

Connected through hyperedge HE-5 (induced by source paper "capacity of sum networks for different message alphabets"):
  with members:
    - "on network coding for sum networks"
    - "network coding for computing cut set bounds"
    - "linear codes target function classes and network computing capacity"
    - "communicating the sum of sources over a network"

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)