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 "top tree compression of tries"):
  Abstract: We present a compressed representation of tries based on top tree compression [ICALP 2013] that works on a standard, comparison-based, pointer machine model of computation and supports efficient prefix search queries. Namely, we show how to preprocess a set of strings of total length $n$ over an alphabet of size $\sigma$ into a compressed data structure of worst-case optimal size $O(n/\log_\sigma n)$ that given a pattern string $P$ of length $m$ determines if $P$ is a prefix of one of the strings in time $O(\min(m\log \sigma,m + \log n))$. We show that this query time is in fact optimal regardless of the size of the data structure. #R##N#Existing solutions either use $\Omega(n)$ space or use word RAM bit tricks (i.e. do not work on a pointer machine). Our result is the first solution on a pointer machine that achieves worst-case $o(n)$ space. Along the way, we develop several interesting data structures that work on a pointer machine and are of independent interest. These include an optimal data structure for random access to a grammar-compressed string and an optimal data structure for a variant of the level ancestor problem.

Includes members:
  Member "dynamic packed compact tries revisited":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dynamic path decomposed tries")
  Member "universal compressed text indexing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "towards a definitive measure of repetitiveness")
  Member "packed compact tries a fast and efficient data structure for online string processing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dynamic path decomposed tries")
  Member "linear size cdawg new repetition aware indexing and grammar compression":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "suffix trees dawgs and cdawgs for forward and backward tries")
  Member "time space trade offs for lempel ziv compressed indexing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "towards a definitive measure of repetitiveness")
  Member "compressed indexing with signature grammars":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards a definitive measure of repetitiveness")
  Member "deterministic indexing for packed strings":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "improved compressed string dictionaries")
  Member "composite repetition aware data structures":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on extensions of maximal repeats in compressed strings")

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)