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: "balanced families of perfect hash functions and their applications"
  Abstract: The construction of perfect hash functions is a well-studied topic. In this paper, this concept is generalized with the following definition. We say that a family of functions from $[n]$ to $[k]$ is a $\delta$-balanced $(n,k)$-family of perfect hash functions if for every $S \subseteq [n]$, $|S|=k$, the number of functions that are 1-1 on $S$ is between $T/\delta$ and $\delta T$ for some constant $T>0$. The standard definition of a family of perfect hash functions requires that there will be at least one function that is 1-1 on $S$, for each $S$ of size $k$. In the new notion of balanced families, we require the number of 1-1 functions to be almost the same (taking $\delta$ to be close to 1) for every such $S$. Our main result is that for any constant $\delta > 1$, a $\delta$-balanced $(n,k)$-family of perfect hash functions of size $2^{O(k \log \log k)} \log n$ can be constructed in time $2^{O(k \log \log k)} n \log n$. Using the technique of color-coding we can apply our explicit constructions to devise approximation algorithms for various counting problems in graphs. In particular, we exhibit a deterministic polynomial time algorithm for approximating both the number of simple paths of length $k$ and the number of simple cycles of size $k$ for any $k \leq O(\frac{\log n}{\log \log \log n})$ in a graph with $n$ vertices. The approximation is up to any fixed desirable relative error.

Connected through hyperedge HE-1 (induced by source paper "a graphblas approach for subgraph counting"):
  with members:
    - "design principles for sparse matrix multiplication on the gpu"
    - "high performance massive subgraph counting using pipelined adaptive group communication"
    - "accelerating pagerank using partition centric processing"
    - "subgraph counting color coding beyond trees"
    - "the reverse cuthill mckee algorithm in distributed memory"
    - "mathematical foundations of the graphblas"
    - "from nosql accumulo to newsql graphulo design and utility of graph algorithms inside a bigtable database"
    - "ringo interactive graph analytics on big memory machines"

Connected through hyperedge HE-2 (induced by source paper "extensor coding"):
  with members:
    - "homomorphisms are a good basis for counting small subgraphs"
    - "a dichotomy theorem for nonuniform csps"
    - "the proof of csp dichotomy conjecture"
    - "clifford algebras meet tree decompositions"
    - "complexity of counting subgraphs only the boundedness of the vertex cover number counts"
    - "mixing color coding related techniques"
    - "efficient computation of representative sets with applications in parameterized and exact algorithms"
    - "narrow sieves for parameterized paths and packings"

Connected through hyperedge HE-3 (induced by source paper "waring rank parameterized and exact algorithms"):
  with members:
    - "fast exact algorithms using hadamard product of polynomials"
    - "extensor coding"
    - "barriers for rank methods in arithmetic complexity"
    - "designing deterministic polynomial space algorithms by color coding multivariate polynomials"
    - "the border support rank of two by two matrix multiplication is seven"
    - "no occurrence obstructions in geometric complexity theory"
    - "nash social welfare matrix permanent and stable polynomials"
    - "graph isomorphism in quasipolynomial time"

Connected through hyperedge HE-4 (induced by source paper "generalized metric repair on graphs"):
  with members:
    - "metric violation distance revisited and extended"
    - "extensor coding"
    - "unsupervised metric learning in presence of missing data"
    - "fully dynamic all pairs shortest paths with worst case update time revisited"
    - "improved hardness for cut interdiction and firefighter problems"
    - "cops robbers and threatening skeletons padded decomposition for minor free graphs"
    - "exact matrix completion via convex optimization"

Connected through hyperedge HE-5 (induced by source paper "fast exact algorithms using hadamard product of polynomials"):
  with members:
    - "on the hardness of the noncommutative determinant"
    - "homogeneous formulas and symmetric polynomials"
    - "arithmetic circuits and the hadamard product of polynomials"

Connected through hyperedge HE-6 (induced by source paper "high performance massive subgraph counting using pipelined adaptive group communication"):
  with members:
    - "subgraph counting color coding beyond trees"

Connected through hyperedge HE-7 (induced by source paper "tensor network complexity of multilinear maps"):
  with members:
    - "spectral methods from tensor networks"
    - "in datacenter performance analysis of a tensor processing unit"
    - "homomorphisms are a good basis for counting small subgraphs"
    - "matrix multiplication trilinear decompositions apa algorithms and summation"
    - "sparse tensor algebra as a parallel programming model"
    - "a framework for practical parallel fast matrix multiplication"
    - "powers of tensors and fast matrix multiplication"
    - "lower bounds on the size of semidefinite programming relaxations"

Connected through hyperedge HE-8 (induced by source paper "counting small subgraphs in multi layer networks"):
  with members:
    - "homomorphisms are a good basis for counting small subgraphs"
    - "complexity of counting subgraphs only the boundedness of the vertex cover number counts"
    - "the challenges of unbounded treewidth in parameterised subgraph counting problems"
    - "the parameterised complexity of counting connected subgraphs and graph motifs"

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)