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 "algorithmically generating new algebraic features of polynomial systems for machine learning"):
  Abstract: There are a variety of choices to be made in both computer algebra systems (CASs) and satisfiability modulo theory (SMT) solvers which can impact performance without affecting mathematical correctness. Such choices are candidates for machine learning (ML) approaches, however, there are difficulties in applying standard ML techniques, such as the efficient identification of ML features from input data which is typically a polynomial system. Our focus is selecting the variable ordering for cylindrical algebraic decomposition (CAD), an important algorithm implemented in several CASs, and now also SMT-solvers. We created a framework to describe all the previously identified ML features for the problem and then enumerated all options in this framework to automatically generation many more features. We validate the usefulness of these with an experiment which shows that an ML choice for CAD variable ordering is superior to those made by human created heuristics, and further improved with these additional features. We expect that this technique of feature generation could be useful for other choices related to CAD, or even choices for other algorithms with polynomial systems for input.

Includes members:
  Member "using machine learning to improve cylindrical algebraic decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deciding the consistency of non linear real arithmetic constraints with a conflict driven search using cylindrical algebraic coverings")
  Member "comparing machine learning models to choose the variable ordering for cylindrical algebraic decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deciding the consistency of non linear real arithmetic constraints with a conflict driven search using cylindrical algebraic coverings")
  Member "theoryguru a mathematica package to apply quantifier elimination technology to economics":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deciding the consistency of non linear real arithmetic constraints with a conflict driven search using cylindrical algebraic coverings")
  Member "non linear real arithmetic benchmarks derived from automated reasoning in economics":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cylindrical algebraic decomposition with equational constraints")
  Member "machine learning for mathematical software":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "cylindrical algebraic decomposition with equational constraints")
  Member "symbolic versus numerical computation and visualization of parameter regions for multistationarity of biological networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cylindrical algebraic decomposition with equational constraints")
  Member "a case study on the parametric occurrence of multiple steady states":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deciding the consistency of non linear real arithmetic constraints with a conflict driven search using cylindrical algebraic coverings")
  Member "using machine learning to decide when to precondition cylindrical algebraic decomposition with groebner bases":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "cylindrical algebraic decomposition with equational constraints")

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.SC(Symbolic Computation)