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: "constructing fewer open cells by gcd computation in cad projection"
  Abstract: A new projection operator based on cylindrical algebraic decomposition (CAD) is proposed. The new operator computes the intersection of projection factor sets produced by different CAD projection orders. In other words, it computes the gcd of projection polynomials in the same variables produced by different CAD projection orders. We prove that the new operator still guarantees obtaining at least one sample point from every connected component of the highest dimension, and therefore, can be used for testing semi-definiteness of polynomials. Although the complexity of the new method is still doubly exponential, in many cases, the new operator does produce smaller projection factor sets and fewer open cells. Some examples of testing semi-definiteness of polynomials, which are difficult to be solved by existing tools, have been worked out efficiently by our program based on the new method.

Connected through hyperedge HE-1 (induced by source paper "solving satisfiability of polynomial formulas by sample cell projection"):
  with members:
    - "a cdcl style calculus for solving non linear constraints"
    - "open weak cad and its applications"

Connected through hyperedge HE-2 (induced by source paper "cylindrical algebraic decomposition with equational constraints"):
  with members:
    - "identifying the parametric occurrence of multiple steady states for some biological networks"
    - "using machine learning to improve cylindrical algebraic decomposition"
    - "theoryguru a mathematica package to apply quantifier elimination technology to economics"
    - "non linear real arithmetic benchmarks derived from automated reasoning in economics"
    - "machine learning for mathematical software"
    - "towards incremental cylindrical algebraic decomposition in maple"
    - "symbolic versus numerical computation and visualization of parameter regions for multistationarity of biological networks"
    - "a case study on the parametric occurrence of multiple steady states"

Connected through hyperedge HE-3 (induced by source paper "using machine learning to improve cylindrical algebraic decomposition"):
  with members:
    - "machine learning for mathematical software"
    - "symbolic versus numerical computation and visualization of parameter regions for multistationarity of biological networks"
    - "a case study on the parametric occurrence of multiple steady states"
    - "need polynomial systems be doubly exponential"
    - "using machine learning to decide when to precondition cylindrical algebraic decomposition with groebner bases"
    - "truth table invariant cylindrical algebraic decomposition"
    - "the complexity of cylindrical algebraic decomposition with respect to polynomial degree"
    - "improving the use of equational constraints in cylindrical algebraic decomposition"

Connected through hyperedge HE-4 (induced by source paper "truth table invariant cylindrical algebraic decomposition"):
  with members:
    - "improving the use of equational constraints in cylindrical algebraic decomposition"
    - "truth table invariant cylindrical algebraic decomposition by regular chains"
    - "applying machine learning to the problem of choosing a heuristic to select the variable ordering for cylindrical algebraic decomposition"
    - "choosing a variable ordering for truth table invariant cylindrical algebraic decomposition by incremental triangular decomposition"
    - "cylindrical algebraic decomposition using local projections"
    - "using the distribution of cells by dimension in a cylindrical algebraic decomposition"
    - "problem formulation for truth table invariant cylindrical algebraic decomposition by incremental triangular decomposition"
    - "using the regular chains library to build cylindrical algebraic decompositions by projecting and lifting"

Connected through hyperedge HE-5 (induced by source paper "the complexity of cylindrical algebraic decomposition with respect to polynomial degree"):
  with members:
    - "need polynomial systems be doubly exponential"
    - "using machine learning to decide when to precondition cylindrical algebraic decomposition with groebner bases"
    - "truth table invariant cylindrical algebraic decomposition"
    - "improving the use of equational constraints in cylindrical algebraic decomposition"
    - "truth table invariant cylindrical algebraic decomposition by regular chains"
    - "applying machine learning to the problem of choosing a heuristic to select the variable ordering for cylindrical algebraic decomposition"
    - "cylindrical algebraic decomposition using local projections"
    - "using the distribution of cells by dimension in a cylindrical algebraic decomposition"

Connected through hyperedge HE-6 (induced by source paper "need polynomial systems be doubly exponential"):
  with members:
    - "truth table invariant cylindrical algebraic decomposition"
    - "the complexity of cylindrical algebraic decomposition with respect to polynomial degree"
    - "improving the use of equational constraints in cylindrical algebraic decomposition"
    - "truth table invariant cylindrical algebraic decomposition by regular chains"
    - "applying machine learning to the problem of choosing a heuristic to select the variable ordering for cylindrical algebraic decomposition"
    - "cylindrical algebraic decomposition using local projections"
    - "using the distribution of cells by dimension in a cylindrical algebraic decomposition"
    - "problem formulation for truth table invariant cylindrical algebraic decomposition by incremental triangular decomposition"

Connected through hyperedge HE-7 (induced by source paper "using machine learning to decide when to precondition cylindrical algebraic decomposition with groebner bases"):
  with members:
    - "need polynomial systems be doubly exponential"
    - "truth table invariant cylindrical algebraic decomposition"
    - "the complexity of cylindrical algebraic decomposition with respect to polynomial degree"
    - "improving the use of equational constraints in cylindrical algebraic decomposition"
    - "truth table invariant cylindrical algebraic decomposition by regular chains"
    - "applying machine learning to the problem of choosing a heuristic to select the variable ordering for cylindrical algebraic decomposition"
    - "choosing a variable ordering for truth table invariant cylindrical algebraic decomposition by incremental triangular decomposition"
    - "cylindrical algebraic decomposition using local projections"

Connected through hyperedge HE-8 (induced by source paper "open weak cad and its applications"):
  with members:
    - "proving inequalities and solving global optimization problems via simplified cad projection"

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.SC(Symbolic Computation)