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: "memetic search for overlapping topics based on a local evaluation of link communities"
  Abstract: In spite of recent advances in field delineation methods, bibliometricians still don't know the extent to which their topic detection algorithms reconstruct `ground truths', i.e., thematic structures in the scientific literature. In this paper, we demonstrate a new approach to the delineation of thematic structures that attempts to match the algorithm to theoretically derived and empirically observed properties all thematic structures have in common. We cluster citation links rather than publication nodes, use predominantly local information and search for communities of links starting from seed subgraphs in order to allow for pervasive overlaps of topics. We evaluate sets of links with a new cost function and assume that local minima in the cost landscape correspond to link communities. Because this cost landscape has many local minima we define a valid community as the community with the lowest minimum within a certain range. Since finding all valid communities is impossible for large networks, we designed a memetic algorithm that combines probabilistic evolutionary strategies with deterministic local searches. We apply our approach to a network of about 15,000 Astronomy and Astrophysics papers published 2010 and their cited sources, and to a network of about 100,000 Astronomy and Astrophysics papers (published 2003---2010) which are linked through direct citations.

Connected through hyperedge HE-1 (induced by source paper "how to interpret algorithmically constructed topical structures of research specialties a case study comparing an internal and an external mapping of the topical structure of invasion biology"):
  with members:
    - "from louvain to leiden guaranteeing well connected communities"
    - "granularity of algorithmically constructed publication level classifications of research publications identification of topics"
    - "algorithmically generated subject categories based on citation relations an empirical micro study using papers on overall water splitting"
    - "which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge"
    - "mutual information based labelling and comparing clusters"
    - "clustering scientific publications based on citation relations a systematic comparison of different methods"
    - "a new methodology for constructing a publication level classification system of science"

Connected through hyperedge HE-2 (induced by source paper "communities as well separated subgraphs with cohesive cores identification of core periphery structures in link communities"):
  with members:
    - "hyperbolae are no hyperbole modelling communities that are not cliques"
    - "identification of core periphery structure in networks"
    - "overlapping community detection in networks the state of the art and comparative study"
    - "defining and evaluating network communities based on ground truth"
    - "efficient and principled method for detecting communities in networks"
    - "empirical comparison of algorithms for network community detection"

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.SI(Social and Information Networks)