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 "assessing the computational complexity of multi layer subgraph detection"):
  Abstract: Multi-layer graphs consist of several graphs (layers) over the same vertex set. They are motivated by real-world problems where entities (vertices) are associated via multiple types of relationships (edges in different layers). We chart the border of computational (in)tractability for the class of subgraph detection problems on multi-layer graphs, including fundamental problems such as maximum matching, finding certain clique relaxations (motivated by community detection), or path problems. Mostly encountering hardness results, sometimes even for two or three layers, we can also spot some islands of tractability.

Includes members:
  Member "stream graphs and link streams for the modeling of interactions over time":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "finding temporal patterns using algebraic fingerprints")
  Member "simultaneous feedback vertex set a parameterized perspective":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an improved fpt algorithm for independent feedback vertex set")
  Member "an introduction to temporal graphs an algorithmic perspective":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "graph generators state of the art and open challenges")
  Member "on the k anonymization of time varying and multi layer social graphs":
    also connected through other hyperedges:
      (none)
  Member "the parameterized complexity of k biclique":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "parameterized inapproximability for steiner orientation by gap amplification")
  Member "towards optimal and expressive kernelization for d hitting set":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimal size problem kernels for d hitting set in linear time and space")
  Member "clustering on multi layer graphs via subspace analysis on grassmann manifolds":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning graphs from data a signal representation perspective")
  Member "clustering with multi layer graphs a spectral perspective":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "community detection on mixture multi layer networks via regularized tensor decomposition")

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.CC(Computational Complexity)