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: "on prefix sorting finite automata"
  Abstract: Being able to efficiently test the membership of a word in a formal language is, arguably, one of the most fundamental problems in computer science. In this paper, we combine techniques from string processing (specifically, prefix-sorting) and automata theory (specifically, DFA minimization) to speed up solutions for this problem on languages described by finite automata. Prefix sorting can be generalized to objects more complex than strings: the recent notion of Wheeler graph extends this concept to labeled graphs such as finite-state automata. A Wheeler graph admits a co-lexicographic ordering of its nodes and opens up the possibility of building fast and small data structures supporting powerful path queries on the graph (i.e. substring closure of the accepting language when the graph represents a NFA). However, while several structures including strings, trees, and de Bruijn graphs can always be prefix-sorted in linear time, the situation on general graphs is more complicated: not all graphs admit such an ordering, and a recent result shows that the problem of identifying them is NP-complete even for acyclic NFAs. In this paper, we provide several results showing that the problem becomes tractable on DFAs. Our results include polynomial-time algorithms to (i) recognize and prefix-sort Wheeler finite automata (even admitting some limited amount of nondeterminism), (ii) minimize Wheeler DFAs, and (iii) compute the minimum Wheeler DFA recognizing the same language of any acyclic DFA. Our last contribution is a big step towards a complete solution to the (hard) problem of indexing graphs for efficient path queries: our minimization theorem essentially solves the deterministic-acyclic case with a solution of provably minimum size.

Connected through hyperedge HE-1 (induced by source paper "graphs cannot be indexed in polynomial time for sub quadratic time string matching unless seth fails"):
  with members:
    - "regular languages meet prefix sorting"
    - "on the hardness and inapproximability of recognizing wheeler graphs"
    - "on the hardness of set disjointness and set intersection with bounded universe"
    - "lower bounds for text indexing with mismatches and differences"
    - "indexing variation graphs"
    - "distributed pcp theorems for hardness of approximation in p"
    - "improving viterbi is hard better runtimes imply faster clique algorithms"
    - "the gremlin graph traversal machine and language invited talk"

Connected through hyperedge HE-2 (induced by source paper "on the hardness and inapproximability of recognizing wheeler graphs"):
  with members:
    - "tunneling on wheeler graphs"
    - "succinct dictionary matching with no slowdown"

Connected through hyperedge HE-3 (induced by source paper "on the complexity of exact pattern matching in graphs determinism and zig zag matching"):
  with members:
    - "on the hardness and inapproximability of recognizing wheeler graphs"
    - "on the complexity of exact pattern matching in graphs binary strings and bounded degree"

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)