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: "mapping topics and topic bursts in pnas"
  Abstract: Scientific research is highly dynamic. New areas of science continually evolve; others gain or lose importance, merge, or split. Due to the steady increase in the number of scientific publications, it is hard to keep an overview of the structure and dynamic development of one's own field of science, much less all scientific domains. However, knowledge of "hot" topics, emergent research frontiers, or change of focus in certain areas is a critical component of resource allocation decisions in research laboratories, governmental institutions, and corporations. This paper demonstrates the utilization of Kleinberg's burst detection algorithm, co-word occurrence analysis, and graph layout techniques to generate maps that support the identification of major research topics and trends. The approach was applied to analyze and map the complete set of papers published in PNAS in the years 1982-2001. Six domain experts examined and commented on the resulting maps in an attempt to reconstruct the evolution of major research areas covered by PNAS.

Connected through hyperedge HE-1 (induced by source paper "early detection of research trends"):
  with members:
    - "a bimodal network approach to model topic dynamics"
    - "maps of computer science"
    - "interactive overlays of journals and the measurement of interdisciplinarity on the basis of aggregated journal journal citations"
    - "subgraph frequencies mapping the empirical and extremal geography of large graph collections"
    - "identifying discriminating network motifs in youtube spam"
    - "the author topic model for authors and documents"
    - "development of computer science disciplines a social network analysis approach"
    - "interactive overlays a new method for generating global journal maps from web of science data"

Connected through hyperedge HE-2 (induced by source paper "research topics map rtopmap"):
  with members:
    - "citation analysis with microsoft academic"
    - "quantifying the diaspora of knowledge in the last century"
    - "putting recommendations on the map visualizing clusters and relations"

Connected through hyperedge HE-3 (induced by source paper "maps of computer science"):
  with members:
    - "syntactic topic models"
    - "putting recommendations on the map visualizing clusters and relations"
    - "lexrank graph based lexical centrality as salience in text summarization"

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.IR(Information Retrieval)