human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "fast partial distance estimation and applications"):
  Abstract: We study approximate distributed solutions to the weighted {\it all-pairs-shortest-paths} (APSP) problem in the CONGEST model. We obtain the following results. #R##N#$1.$ A deterministic $(1+o(1))$-approximation to APSP in $\tilde{O}(n)$ rounds. This improves over the best previously known algorithm, by both derandomizing it and by reducing the running time by a $\Theta(\log n)$ factor. #R##N#In many cases, routing schemes involve relabeling, i.e., assigning new names to nodes and require that these names are used in distance and routing queries. It is known that relabeling is necessary to achieve running times of $o(n/\log n)$. In the relabeling model, we obtain the following results. #R##N#$2.$ A randomized $O(k)$-approximation to APSP, for any integer $k>1$, running in $\tilde{O}(n^{1/2+1/k}+D)$ rounds, where $D$ is the hop diameter of the network. This algorithm simplifies the best previously known result and reduces its approximation ratio from $O(k\log k)$ to $O(k)$. Also, the new algorithm uses uses labels of asymptotically optimal size, namely $O(\log n)$ bits. #R##N#$3.$ A randomized $O(k)$-approximation to APSP, for any integer $k>1$, running in time $\tilde{O}((nD)^{1/2}\cdot n^{1/k}+D)$ and producing {\it compact routing tables} of size $\tilde{O}(n^{1/k})$. The node lables consist of $O(k\log n)$ bits. This improves on the approximation ratio of $\Theta(k^2)$ for tables of that size achieved by the best previously known algorithm, which terminates faster, in $\tilde{O}(n^{1/2+1/k}+D)$ rounds.

Includes members:
  Member "an almost tight distributed algorithm for computing single source shortest paths":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "parallel approximate undirected shortest paths via low hop emulators")
  Member "approximation of distances and shortest paths in the broadcast congest clique":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "exponentially faster shortest paths in the congested clique")
  Member "distributed approximation algorithms for weighted shortest paths":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed edge connectivity in sublinear time")
  Member "improved distributed steiner forest construction":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "hardness of distributed optimization")
  Member "efficient computation of distance sketches in distributed networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a deterministic almost tight distributed algorithm for approximating single source shortest paths")
  Member "distributed verification and hardness of distributed approximation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "beyond alice and bob improved inapproximability for maximum independent set in congest")
  Member "faster approximation schemes for fractional multicommodity flow problems via dynamic graph algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "all pairs shortest paths using bridging sets and rectangular matrix multiplication":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")

Question: Please tell me which class the source paper 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)