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: "distributed strong diameter network decomposition"
  Abstract: For a pair of positive parameters $D,\chi$, a partition ${\cal P}$ of the vertex set $V$ of an $n$-vertex graph $G = (V,E)$ into disjoint clusters of diameter at most $D$ each is called a $(D,\chi)$ network decomposition, if the supergraph ${\cal G}({\cal P})$, obtained by contracting each of the clusters of ${\cal P}$, can be properly $\chi$-colored. The decomposition ${\cal P}$ is said to be strong (resp., weak) if each of the clusters has strong (resp., weak) diameter at most $D$, i.e., if for every cluster $C \in {\cal P}$ and every two vertices $u,v \in C$, the distance between them in the induced graph $G(C)$ of $C$ (resp., in $G$) is at most $D$. #R##N#Network decomposition is a powerful construct, very useful in distributed computing and beyond. It was shown by Awerbuch \etal \cite{AGLP89} and Panconesi and Srinivasan \cite{PS92}, that strong $(2^{O(\sqrt{\log n})},2^{O(\sqrt{\log n})})$ network decompositions can be computed in $2^{O(\sqrt{\log n})}$ distributed time. Linial and Saks \cite{LS93} devised an ingenious randomized algorithm that constructs {\em weak} $(O(\log n),O(\log n))$ network decompositions in $O(\log^2 n)$ time. It was however open till now if {\em strong} network decompositions with both parameters $2^{o(\sqrt{\log n})}$ can be constructed in distributed $2^{o(\sqrt{\log n})}$ time. #R##N#In this paper we answer this long-standing open question in the affirmative, and show that strong $(O(\log n),O(\log n))$ network decompositions can be computed in $O(\log^2 n)$ time. We also present a tradeoff between parameters of our network decomposition. Our work is inspired by and relies on the "shifted shortest path approach", due to Blelloch \etal \cite{BGKMPT11}, and Miller \etal \cite{MPX13}. These authors developed this approach for PRAM algorithms for padded partitions. We adapt their approach to network decompositions in the distributed model of computation.

Connected through hyperedge HE-1 (induced by source paper "on the use of randomness in local distributed graph algorithms"):
  with members:
    - "deterministic distributed edge coloring via hypergraph maximal matching"
    - "on derandomizing local distributed algorithms"
    - "distributed degree splitting edge coloring and orientations"
    - "an exponential separation between randomized and deterministic complexity in the local model"
    - "on the complexity of local distributed graph problems"
    - "a deterministic almost tight distributed algorithm for approximating single source shortest paths"
    - "an improved distributed algorithm for maximal independent set"
    - "a lower bound for the distributed lov asz local lemma"

Connected through hyperedge HE-2 (induced by source paper "improved network decompositions using small messages with applications on mis neighborhood covers and beyond"):
  with members:
    - "deterministic distributed dominating set approximation in the congest model"
    - "a fast network decomposition algorithm and its applications to constant time distributed computation"
    - "an improved distributed algorithm for maximal independent set"
    - "parallel graph decompositions using random shifts"
    - "the locality of distributed symmetry breaking"
    - "on the locality of some np complete problems"
    - "near linear work parallel sdd solvers low diameter decomposition and low stretch subgraphs"

Connected through hyperedge HE-3 (induced by source paper "faster distributed shortest path approximations via shortcuts"):
  with members:
    - "near optimal approximate shortest paths and transshipment in distributed and streaming models"
    - "low congestion shortcuts without embedding"
    - "an almost tight distributed algorithm for computing single source shortest paths"
    - "fast partial distance estimation and applications"
    - "almost tight distributed minimum cut algorithms"
    - "distributed approximation algorithms for weighted shortest paths"
    - "cops robbers and threatening skeletons padded decomposition for minor free graphs"
    - "parallel graph decompositions using random shifts"

Connected through hyperedge HE-4 (induced by source paper "efficient distributed computation of mis and generalized mis in linear hypergraphs"):
  with members:
    - "derandomized concentration bounds for polynomials and hypergraph maximal independent set"
    - "derandomizing local distributed algorithms under bandwidth restrictions"
    - "on the complexity of local distributed graph problems"
    - "an improved distributed algorithm for maximal independent set"
    - "distributed symmetry breaking in hypergraphs"
    - "on computing maximal independent sets of hypergraphs in parallel"
    - "the locality of distributed symmetry breaking"

Connected through hyperedge HE-5 (induced by source paper "fast distributed approximation for max cut"):
  with members:
    - "efficient algorithms for constructing very sparse spanners and emulators"
    - "a distributed 2 epsilon approximation for vertex cover in o log delta epsilon log log delta rounds"
    - "randomized composable core sets for distributed submodular maximization"
    - "a deterministic almost tight distributed algorithm for approximating single source shortest paths"
    - "a new framework for distributed submodular maximization"
    - "large cuts with local algorithms on triangle free graphs"
    - "distributed approximation algorithms for weighted shortest paths"
    - "streaming lower bounds for approximating max cut"

Connected through hyperedge HE-6 (induced by source paper "on the complexity of local distributed graph problems"):
  with members:
    - "polynomial lower bound for distributed graph coloring in a weak local model"
    - "distributed degree splitting edge coloring and orientations"
    - "distributed delta 1 coloring in sublogarithmic rounds"
    - "an exponential separation between randomized and deterministic complexity in the local model"
    - "a hierarchy of local decision"
    - "a fast network decomposition algorithm and its applications to constant time distributed computation"
    - "local conflict coloring"
    - "node labels in local decision"

Connected through hyperedge HE-7 (induced by source paper "efficient algorithms for constructing very sparse spanners and emulators"):
  with members:
    - "the greedy spanner is existentially optimal"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "hopsets with constant hopbound and applications to approximate shortest paths"
    - "a linear size logarithmic stretch path reporting distance oracle for general graphs"
    - "very sparse additive spanners and emulators"
    - "the 4 3 additive spanner exponent is tight"
    - "an entropy based proof for the moore bound for irregular graphs"
    - "parallel graph decompositions using random shifts"

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.DS(Data Structures and Algorithms)