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 "internal dictionary matching"):
  Abstract: We introduce data structures answering queries concerning the occurrences of patterns from a given dictionary $\mathcal{D}$ in fragments of a given string $T$ of length $n$. The dictionary is internal in the sense that each pattern in $\mathcal{D}$ is given as a fragment of $T$. This way, $\mathcal{D}$ takes space proportional to the number of patterns $d=|\mathcal{D}|$ rather than their total length, which could be $\Theta(n\cdot d)$. #R##N#In particular, we consider the following types of queries: reporting and counting all occurrences of patterns from $\mathcal{D}$ in a fragment $T[i..j]$ and reporting distinct patterns from $\mathcal{D}$ that occur in $T[i..j]$. We show how to construct, in $\mathcal{O}((n+d) \log^{\mathcal{O}(1)} n)$ time, a data structure that answers each of these queries in time $\mathcal{O}(\log^{\mathcal{O}(1)} n+|output|)$. #R##N#The case of counting patterns is much more involved and needs a combination of a locally consistent parsing with orthogonal range searching. Reporting distinct patterns, on the other hand, uses the structure of maximal repetitions in strings. Finally, we provide tight---up to subpolynomial factors---upper and lower bounds for the case of a dynamic dictionary.

Includes members:
  Member "computing all distinct squares in linear time for integer alphabets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on longest common property preserved substring queries")
  Member "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "wavelet trees meet suffix trees":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "translating between wavelet tree and wavelet matrix construction")
  Member "internal pattern matching queries in a text and applications":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "string synchronizing sets sublinear time bwt construction and optimal lce data structure")
  Member "recompression a simple and powerful technique for word equations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a survey on string constraint solving")
  Member "a linear time algorithm for seeds computation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "experimental evaluation of algorithms for computing quasiperiods")
  Member "faster fully compressed pattern matching by recompression":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "grammar compression with probabilistic context free grammar")

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)