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 "recompression a simple and powerful technique for word equations"):
  Abstract: In this paper we present an application of a simple technique of local recompression, previously developed by the author in the context of compressed membership problems and compressed pattern matching, to word equations. The technique is based on local modification of variables (replacing X by aX or Xa) and iterative replacement of pairs of letters appearing in the equation by a `fresh' letter, which can be seen as a bottom-up compression of the solution of the given word equation, to be more specific, building an SLP (Straight-Line Programme) for the solution of the word equation. #R##N#Using this technique we give a new, independent and self-contained proofs of most of the known results for word equations. To be more specific, the presented (nondeterministic) algorithm runs in O(n log n) space and in time polynomial in log N, where N is the size of the length-minimal solution of the word equation. The presented algorithm can be easily generalised to a generator of all solutions of the given word equation (without increasing the space usage). Furthermore, a further analysis of the algorithm yields a doubly exponential upper bound on the size of the length-minimal solution. The presented algorithm does not use exponential bound on the exponent of periodicity. Conversely, the analysis of the algorithm yields an independent proof of the exponential bound on exponent of periodicity. #R##N#We believe that the presented algorithm, its idea and analysis are far simpler than all previously applied. Furthermore, thanks to it we can obtain a unified and simple approach to most of known results for word equations. #R##N#As a small additional result we show that for O(1) variables (with arbitrary many appearances in the equation) word equations can be solved in linear space, i.e. they are context-sensitive.

Includes members:
  Member "the complexity of compressed membership problems for finite automata":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "unary pushdown automata and straight line programs")
  Member "a really simple approximation of smallest grammar":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "towards a definitive measure of repetitiveness")
  Member "finding all solutions of equations in free groups and monoids with involution":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "solution sets for equations over free groups are edt0l languages icalp 2015 version")
  Member "approximation of grammar based compression via recompression":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a survey on string constraint solving")
  Member "approximation of smallest linear tree grammar":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "repair in compressed space and time")
  Member "context unification is in pspace":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "matching patterns with variables")
  Member "one variable word equations in linear time":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "matching patterns with variables")
  Member "faster fully compressed pattern matching by recompression":
    also connected through other hyperedges:
      - Hyperedge HE-8 (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.FL(Formal Languages and Automata Theory)