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 "contracting to a longest path in h free graphs"):
  Abstract: We prove two dichotomy results for detecting long paths as patterns in a given graph. The NP-hard problem Longest Induced Path is to determine the longest induced path in a graph. The NP-hard problem Longest Path Contractibility is to determine the longest path to which a graph can be contracted to. By combining known results with new results we completely classify the computational complexity of both problems for $H$-free graphs. Our main focus is on the second problem, for which we design a general contractibility technique that enables us to reduce the problem to a matching problem.

Includes members:
  Member "on the parameterized complexity of contraction to generalization of trees":
    also connected through other hyperedges:
      (none)
  Member "independent feedback vertex set for p_5 free graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on cycle transversals and their connected variants in the absence of a small linear forest")
  Member "contracting bipartite graphs to paths and cycles":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "connected vertex cover for sp_1 p_5 free graphs")
  Member "polynomial time algorithms for the longest induced path and induced disjoint paths problems on graphs of bounded mim width":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a meta algorithm for solving connectivity and acyclicity constraints on locally checkable properties parameterized by graph width measures")
  Member "a faster fpt algorithm for bipartite contraction":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an improved kernel for the cycle contraction problem")
  Member "obtaining planarity by contracting few edges":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hitting topological minor models in planar graphs is fixed parameter tractable")
  Member "finding small separators in linear time via treewidth reduction":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fixed parameter tractability of counting small minimum s t cuts")
  Member "contracting graphs to paths and trees":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "multistage graph problems on a global budget")

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)