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: "modelling the effectiveness of curriculum in educational systems using bayesian networks"
  Abstract: In recent years, online education has been considered as one of the most widely used IT services. Researchers in this field face many challenges in the realm of Electronic learning services. Nowadays, many researchers in the field of learning and eLearning study curriculum planning, considering its complexity and the various numbers of effective parameters. The success of a curriculum is a multifaceted issue which needs analytical modelling for precise simulations of the different learning scenarios. In this paper, parameters involved in the learning process will be identified and a curriculum will be propounded. Furthermore, a Curriculum model will be proposed using the behavior of the user, based on the logs of the server. This model will estimate the success rate of the users while taking courses. Authentic Bayesian networks have been used for modelling. In order to evaluate the proposed model, the data of three consecutive semesters of 117 MS IT Students of E-Learning Center of Amirkabir University of Technology has been used. The assessment clarifies the effects of various parameters on the success of curriculum planning.

Connected through hyperedge HE-1 (induced by source paper "the role of artificial intelligence ai in adaptive elearning system aes content formation risks and opportunities involved"):
  with members:
    - "mining educational data to analyze students performance"

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.CY(Computers and Society)