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: "general compact labeling schemes for dynamic trees"
  Abstract: Let $F$ be a function on pairs of vertices. An {\em $F$- labeling scheme} is composed of a {\em marker} algorithm for labeling the vertices of a graph with short labels, coupled with a {\em decoder} algorithm allowing one to compute $F(u,v)$ of any two vertices $u$ and $v$ directly from their labels. As applications for labeling schemes concern mainly large and dynamically changing networks, it is of interest to study {\em distributed dynamic} labeling schemes. This paper investigates labeling schemes for dynamic trees. #R##N#This paper presents a general method for constructing labeling schemes for dynamic trees. Our method is based on extending an existing {\em static} tree labeling scheme to the dynamic setting. This approach fits many natural functions on trees, such as ancestry relation, routing (in both the adversary and the designer port models), nearest common ancestor etc.. Our resulting dynamic schemes incur overheads (over the static scheme) on the label size and on the communication complexity. Informally, for any function $k(n)$ and any static $F$-labeling scheme on trees, we present an $F$-labeling scheme on dynamic trees incurring multiplicative overhead factors #R##N#(over the static scheme) of $O(\log_{k(n)} n)$ on the label size and $O(k(n)\log_{k(n)} n)$ on the amortized message complexity. In particular, by setting $k(n)=n^{\epsilon}$ for any $0<\epsilon<1$, we obtain dynamic labeling schemes with asymptotically optimal label sizes and sublinear amortized message complexity for all the above mentioned functions.

Connected through hyperedge HE-1 (induced by source paper "some problems in compact message passing"):
  with members:
    - "linear size hopsets with small hopbound and distributed routing with low memory"
    - "a self stabilizing general de bruijn graph"
    - "the computational power of beeps"
    - "fast partial distance estimation and applications"
    - "dex self healing expanders"
    - "algorithms for self healing networks"
    - "the forgiving graph a distributed data structure for low stretch under adversarial attack"
    - "the forgiving tree a self healing distributed data structure"

Connected through hyperedge HE-2 (induced by source paper "compact routing messages in self healing trees"):
  with members:
    - "fast and compact self stabilizing verification computation and fault detection of an mst"
    - "self healing computation"
    - "fast and compact distributed verification and self stabilization of a dfs tree"
    - "dex self healing expanders"
    - "edge preserving self healing keeping network backbones densely connected"
    - "algorithms for self healing networks"
    - "the forgiving graph a distributed data structure for low stretch under adversarial attack"
    - "picking up the pieces self healing in reconfigurable networks"

Connected through hyperedge HE-3 (induced by source paper "near optimal adjacency labeling scheme for power law graphs"):
  with members:
    - "adjacency labeling schemes and induced universal graphs"
    - "labeling schemes for bounded degree graphs"
    - "dynamic and multi functional labeling schemes"
    - "community structure in large networks natural cluster sizes and the absence of large well defined clusters"

Connected through hyperedge HE-4 (induced by source paper "dynamic and multi functional labeling schemes"):
  with members:
    - "improved ancestry labeling scheme for trees"
    - "near optimal labeling schemes for nearest common ancestors"
    - "labeling schemes for bounded degree graphs"
    - "succinct data structures for representing equivalence 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.DC(Distributed, Parallel, and Cluster Computing)