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: "compressed range minimum queries"
  Abstract: Given a string $S$ of $n$ integers in $[0,\sigma)$, a range minimum query $\textsf{RMQ}(i, j)$ asks for the index of the smallest integer in $S[i \dots j]$. It is well known that the problem can be solved with a succinct data structure of size $2n + o(n)$ and constant query-time. In this paper we show how to preprocess $S$ into a {\em compressed representation} that allows fast range minimum queries. This allows for {\em sublinear} size data structures with logarithmic query time. The most natural approach is to use string compression and construct a data structure for answering range minimum queries directly on the compressed string. We investigate this approach using grammar compression. We then consider an alternative approach. Even if $S$ is not compressible, its Cartesian tree necessarily is. Therefore, instead of compressing $S$ using string compression, we compress the Cartesian tree of $S$ using tree compression. We show that this approach can be exponentially better than the former, is never worse by more than an $O(\sigma)$ factor (i.e. for constant alphabets it is never asymptotically worse), and can in fact be worse by an $\Omega(\sigma)$ factor.

Connected through hyperedge HE-1 (induced by source paper "balancing straight line programs"):
  with members:
    - "top tree compression of tries"
    - "grammar based compression of unranked trees"
    - "a universal tree balancing theorem"
    - "tree compression with top trees revisited"
    - "compressed subsequence matching and packed tree coloring"
    - "a really simple approximation of smallest grammar"
    - "approximation of grammar based compression via recompression"
    - "faster fully compressed pattern matching by recompression"

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)