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 "an ontological learning management system"):
  Abstract: The current learning systems typically lack the level of metacognitive awareness, self-directed learning, and time management skills. Most of the ontologically based learning management systems are in the proposed phase and those which are developed do not provide the necessary path guidance for proper learning. The systems available are not as adaptive from the viewpoint of the learner as required. Ontology engineering has become an important pillar for knowledge management and representation in recent years. The design, approach, and implementation of ontology in e-learning and m-learning systems have made them more effective. In this paper, we have proposed a system for the betterment of knowledge management and representation of associated data as compared to the previously available learning management systems. Here, we have presented the application and implementation of ontological engineering methodology in the Computer Science domain. For knowledge management, we have created a domain associated ontology which represents knowledge of a single domain. Subsequently, ontology has been created to manage a learner profile so that a learner may be aligned to a proper path of learning. The learner ontology will use the VARK learning model which classifies what kind of learning does the learner requires so that necessary resources could be provided.

Includes members:
  Member "an ontology based adaptive personalized e learning system assisted by software agents on cloud storage":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "semi automatic terminology ontology learning based on topic modeling")
  Member "a hybrid approach using ontology similarity and fuzzy logic for semantic question answering":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "semi automatic terminology ontology learning based on topic modeling")

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.CY(Computers and Society)