human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "fractals for kernelization lower bounds"
  Abstract: The composition technique is a popular method for excluding polynomial-size problem kernels for NP-hard parameterized problems. We present a new technique exploiting triangle-based fractal structures for extending the range of applicability of compositions. Our technique makes it possible to prove new no-polynomial-kernel results for a number of problems dealing with length-bounded cuts. In particular, answering an open question of Golovach and Thilikos [Discrete Optim. 2011], we show that, unless NP $\subseteq$ coNP / poly, the NP-hard Length-Bounded Edge-Cut (LBEC) problem (delete at most $k$ edges such that the resulting graph has no $s$-$t$ path of length shorter than $\ell$) parameterized by the combination of $k$ and $\ell$ has no polynomial-size problem kernel. Our framework applies to planar as well as directed variants of the basic problems and also applies to both edge and vertex deletion problems. Along the way, we show that LBEC remains NP-hard on planar graphs, a result which we believe is interesting in its own right.

Connected through hyperedge HE-1 (induced by source paper "length bounded cuts proper interval graphs and structural parameters"):
  with members:
    - "a more fine grained complexity analysis of finding the most vital edges for undirected shortest paths"
    - "the complexity of finding small separators in temporal graphs"

Connected through hyperedge HE-2 (induced by source paper "a more fine grained complexity analysis of finding the most vital edges for undirected shortest paths"):
  with members:
    - "parameterized approximability of maximizing the spread of influence in networks"
    - "parameterized complexity of edge interdiction problems"
    - "interdiction problems on planar graphs"

Connected through hyperedge HE-3 (induced by source paper "the complexity of finding small separators in temporal graphs"):
  with members:
    - "temporal vertex cover with a sliding time window"
    - "sliding window temporal graph coloring"
    - "listing all maximal k plexes in temporal graphs"
    - "cluster editing for multi layer and temporal graphs"
    - "stream graphs and link streams for the modeling of interactions over time"
    - "on the size and the approximability of minimum temporally connected subgraphs"
    - "adapting the bron kerbosch algorithm for enumerating maximal cliques in temporal graphs"
    - "survivability in time varying networks"

Connected through hyperedge HE-4 (induced by source paper "improved hardness for cut interdiction and firefighter problems"):
  with members:
    - "new integrality gap results for the firefighters problem on trees"
    - "firefighting on trees beyond integrality gaps"
    - "local distribution and the symmetry gap approximability of multiway partitioning problems"
    - "interdiction problems on planar graphs"
    - "hardness of vertex deletion and project scheduling"

Question: Please tell me which class the center node 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)