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: "faster approximate distance queries and compact routing in sparse graphs"
  Abstract: A distance oracle is a compact representation of the shortest distance matrix of a graph. It can be queried to approximate shortest paths between any pair of vertices. Any distance oracle that returns paths of worst-case stretch (2k-1) must require space $\Omega(n^{1 + 1/k})$ for graphs of n nodes. The hard cases that enforce this lower bound are, however, rather dense graphs with average degree \Omega(n^{1/k}). #R##N#We present distance oracles that, for sparse graphs, substantially break the lower bound barrier at the expense of higher query time. For any 1 \leq \alpha \leq n, our distance oracles can return stretch 2 paths using O(m + n^2/\alpha) space and stretch 3 paths using O(m + n^2/\alpha^2) space, at the expense of O(\alpha m/n) query time. By setting appropriate values of \alpha, we get the first distance oracles that have size linear in the size of the graph, and return constant stretch paths in non-trivial query time. The query time can be further reduced to O(\alpha), by using an additional O(m \alpha) space for all our distance oracles, or at the cost of a small constant additive stretch. #R##N#We use our stretch 2 distance oracle to present the first compact routing scheme with worst-case stretch 2. Any compact routing scheme with stretch less than 2 must require linear memory at some nodes even for sparse graphs; our scheme, hence, achieves the optimal stretch with non-trivial memory requirements. Moreover, supported by large-scale simulations on graphs including the AS-level Internet graph, we argue that our stretch-2 scheme would be simple and efficient to implement as a distributed compact routing protocol.

Connected through hyperedge HE-1 (induced by source paper "on the hardness of set disjointness and set intersection with bounded universe"):
  with members:
    - "how hard is it to find honest witnesses"
    - "conditional lower bounds for space time tradeoffs"
    - "data structure lower bounds for document indexing problems"
    - "dynamic set intersection"
    - "popular conjectures imply strong lower bounds for dynamic problems"
    - "on hardness of jumbled indexing"
    - "higher lower bounds from the 3sum conjecture"
    - "approximate distance oracle with constant query time"

Connected through hyperedge HE-2 (induced by source paper "conditional lower bounds for space time tradeoffs"):
  with members:
    - "how hard is it to find honest witnesses"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"
    - "clustered integer 3sum via additive combinatorics"
    - "subtree isomorphism revisited"
    - "if the current clique algorithms are optimal so is valiant s parser"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"
    - "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails"
    - "dynamic set intersection"

Connected through hyperedge HE-3 (induced by source paper "a linear size logarithmic stretch path reporting distance oracle for general graphs"):
  with members:
    - "space efficient path reporting approximate distance oracles"
    - "approximate distance oracle with constant query time"
    - "approximate distance oracles with improved preprocessing time"
    - "ramsey partitions and proximity data structures"
    - "lower stretch spanning trees"

Connected through hyperedge HE-4 (induced by source paper "space efficient path reporting approximate distance oracles"):
  with members:
    - "a linear size logarithmic stretch path reporting distance oracle for general graphs"
    - "approximate distance oracle with constant query time"
    - "cops robbers and threatening skeletons padded decomposition for minor free graphs"
    - "approximate distance oracles with improved query time"
    - "approximate distance oracles with improved preprocessing time"
    - "linear space approximate distance oracles for planar bounded genus and minor free graphs"
    - "ramsey partitions and proximity data structures"
    - "fast construction of nets in low dimensional metrics and their applications"

Connected through hyperedge HE-5 (induced by source paper "linear time compression of bounded genus graphs into information theoretically optimal number of bits"):
  with members:
    - "orderly spanning trees with applications"
    - "compact encodings of planar graphs via canonical orderings and multiple parentheses"
    - "linear time succinct encodings of planar graphs via canonical orderings"
    - "a fast general methodology for information theoretically optimal encodings of graphs"

Connected through hyperedge HE-6 (induced by source paper "bypassing erd h o s girth conjecture hybrid stretch and sourcewise spanners"):
  with members:
    - "on pairwise spanners"
    - "ramsey partitions and proximity data structures"
    - "lower stretch spanning trees"

Connected through hyperedge HE-7 (induced by source paper "shortest paths in microseconds"):
  with members:
    - "fast exact shortest path distance queries on large networks by pruned landmark labeling"
    - "shortest paths in less than a millisecond"

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)