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 "decremental single source shortest paths on undirected graphs in near linear total update time"):
  Abstract: The decremental single-source shortest paths (SSSP) problem concerns maintaining the distances between a given source node s to every node in an n-node m-edge graph G undergoing edge deletions. While its static counterpart can be easily solved in near-linear time, this decremental problem is much more challenging even in the undirected unweighted case. In this case, the classic O(mn) total update time of Even and Shiloach (JACM 1981) has been the fastest known algorithm for three decades. With the loss of a (1 + aepsi;)-approximation factor, the running time was recently improved to O(n2+o(1)) by Bernstein and Roditty (SODA 2011), and more recently to O(n1.8+o(1) + m1+o(1)) by Henzinger, Krinninger, and Nanongkai (SODA 2014). In this paper, we finally bring the running time of this case down to near-linear: We give a (1 + aepsi;)-approximation algorithm with O(m1+o(1)) total update time, thus obtaining near-linear time. Moreover, we obtain O(m1+o(1)log W) time for the weighted case, where the edge weights are integers from 1 to W. The only prior work on weighted graphs in o(mn log W) time is the O(mn0.986 log W)-time algorithm by Henzinger, Krinninger, and Nanongkai (STOC 2014) which works for the general weighted directed case. In contrast to the previous results which rely on maintaining a sparse emulator, our algorithm relies on maintaining a so-called sparse (d, aepsi;)-hop set introduced by Cohen (JACM 2000) in the PRAM literature. A (d, aepsi;)-hop set of a graph G = (V, E) is a set E' of weighted edges such that the distance between any pair of nodes in G can be (1 + aepsi;)-approximated by their d-hop distance (given by a path containing at most d edges) on G'=(V, E a#x222A; E'). Our algorithm can maintain an (no(1), aepsi;)-hop set of near-linear size in near-linear time under edge deletions. It is the first of its kind to the best of our knowledge. To maintain the distances on this hop set, we develop a monotone bounded-hop Even-Shiloach tree. It results from extending and combining the monotone Even-Shiloach tree of Henzinger, Krinninger, and Nanongkai (FOCS 2013) with the bounded-hop SSSP technique of Bernstein (STOC 2013). These two new tools might be of independent interest.

Includes members:
  Member "deterministic partially dynamic single source shortest paths in weighted graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "linear size hopsets with small hopbound and distributed routing with low memory":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "exponentially faster shortest paths in the congested clique")
  Member "thorup zwick emulators are universally optimal hopsets":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deterministic algorithms for decremental approximate shortest paths faster and simpler")
  Member "a hierarchy of lower bounds for sublinear additive spanners":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "exponentially faster shortest paths in the congested clique")
  Member "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "improved algorithms for decremental single source reachability on directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "sublinear time decremental algorithms for single source reachability and shortest paths on directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "approximate distance oracles subject to multiple vertex failures")
  Member "popular conjectures imply strong lower bounds for dynamic problems":
    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.DS(Data Structures and Algorithms)