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: "hitting set for hypergraphs of low vc dimension"
  Abstract: We study the complexity of the Hitting Set problem in set systems (hypergraphs) that avoid certain sub-structures. In particular, we characterize the classical and parameterized complexity of the problem when the Vapnik-Chervonenkis dimension (VC-dimension) of the input is small. VC-dimension is a natural measure of complexity of set systems. Several tractable instances of Hitting Set with a geometric or graph-theoretical flavor are known to have low VC-dimension. In set systems of bounded VC-dimension, Hitting Set is known to admit efficient and almost optimal approximation algorithms (Br\"onnimann and Goodrich, 1995; Even, Rawitz, and Shahar, 2005; Agarwal and Pan, 2014). #R##N#In contrast to these approximation-results, a low VC-dimension does not necessarily imply tractability in the parameterized sense. In fact, we show that Hitting Set is W[1]-hard already on inputs with VC-dimension 2, even if the VC-dimension of the dual set system is also 2. Thus, Hitting Set is very unlikely to be fixed-parameter tractable even in this arguably simple case. This answers an open question raised by King in 2010. For set systems whose (primal or dual) VC-dimension is 1, we show that Hitting Set is solvable in polynomial time. #R##N#To bridge the gap in complexity between the classes of inputs with VC-dimension 1 and 2, we use a measure that is more fine-grained than VC-dimension. In terms of this measure, we identify a sharp threshold where the complexity of Hitting Set transitions from polynomial-time-solvable to NP-hard. The tractable class that lies just under the threshold is a generalization of Edge Cover, and thus extends the domain of polynomial-time tractability of Hitting Set.

Connected through hyperedge HE-1 (induced by source paper "tight bounds for planar strongly connected steiner subgraph with fixed number of terminals and extensions"):
  with members:
    - "fpt inapproximability of directed cut and connectivity problems"
    - "complexity of the steiner network problem with respect to the number of terminals"
    - "the parameterized complexity of finding point sets with hereditary properties"
    - "homomorphisms are a good basis for counting small subgraphs"
    - "parameterized approximation algorithms for directed steiner network problems"
    - "the graph motif problem parameterized by the structure of the input graph"
    - "on subexponential parameterized algorithms for steiner tree and directed subset tsp on planar graphs"
    - "on the parameterized complexity of red blue points separation"

Connected through hyperedge HE-2 (induced by source paper "finding and counting permutations via csps"):
  with members:
    - "improved bounds for testing forbidden order patterns"
    - "pattern avoiding access in binary search trees"
    - "finding small patterns in permutations in linear time"
    - "the computational landscape of permutation patterns"
    - "a fast algorithm for permutation pattern matching based on alternating runs"

Connected through hyperedge HE-3 (induced by source paper "parameterized and approximation complexity of partial vc dimension"):
  with members:
    - "inapproximability of vc dimension and littlestone s dimension"
    - "identification location domination and metric dimension on interval and permutation graphs i bounds"
    - "identification location domination and metric dimension on interval and permutation graphs ii algorithms and complexity"
    - "on the approximability of partial vc dimension"
    - "identifying codes in hereditary classes of graphs and vc dimension"
    - "parameterized approximability of maximizing the spread of influence in networks"
    - "parameterizations of test cover with bounded test sizes"
    - "parameterized study of the test cover problem"

Connected through hyperedge HE-4 (induced by source paper "on the approximability of partial vc dimension"):
  with members:
    - "identifying codes in hereditary classes of graphs and vc dimension"
    - "parameterized approximability of maximizing the spread of influence in networks"
    - "parameterizations of test cover with bounded test sizes"
    - "parameterized study of the test cover problem"

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.DS(Data Structures and Algorithms)