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: "on bibliographic networks"
  Abstract: In the paper we show that the bibliographic data can be transformed into a collection of compatible networks. Using network multiplication different interesting derived networks can be obtained. In defining them an appropriate normalization should be considered. The proposed approach can be applied also to other collections of compatible networks. The networks obtained from the bibliographic data bases can be large (hundreds of thousands of vertices). Fortunately they are sparse and can be still processed relatively fast. We answer the question when the multiplication of sparse networks preserves sparseness. The proposed approaches are illustrated with analyses of collection of networks on the topic "social network" obtained from the Web of Science. The works with large number of co-authors add large complete subgraphs to standard collaboration network thus bluring the collaboration structure. We show that using an appropriate normalization their effect can be neutralized. Among other, we propose a measure of collaborativness of authors with respect to a given bibliography and show how to compute the network of citations between authors and identify citation communities.

Connected through hyperedge HE-1 (induced by source paper "on fractional approach to analysis of linked networks"):
  with members:
    - "a categorization of arguments for counting methods for publication and citation indicators"
    - "a conservation rule for constructing bibliometric network matrices"
    - "constructing bibliometric networks a comparison between full and fractional counting"
    - "full and fractional counting in bibliometric networks"
    - "network analysis of zentralblatt math data"

Connected through hyperedge HE-2 (induced by source paper "temporal bibliographic networks"):
  with members:
    - "an algebraic approach to temporal network analysis based on temporal quantities"
    - "network analysis of zentralblatt math data"
    - "time varying graphs and dynamic networks"

Connected through hyperedge HE-3 (induced by source paper "full and fractional counting in bibliometric networks"):
  with members:
    - "constructing bibliometric networks a comparison between full and fractional counting"
    - "the normalization of co authorship networks in the bibliometric evaluation the government stimulation programs of china and korea"
    - "the normalization of occurrence and co occurrence matrices in bibliometrics using cosine similarities and ochiai coefficients"
    - "network analysis of zentralblatt math data"
    - "a systematic empirical comparison of different approaches for normalizing citation impact indicators"
    - "co occurrence matrices and their applications in information science extending aca to the web environment"

Connected through hyperedge HE-4 (induced by source paper "constructing bibliometric networks a comparison between full and fractional counting"):
  with members:
    - "the normalization of co authorship networks in the bibliometric evaluation the government stimulation programs of china and korea"
    - "field normalized citation impact indicators and the choice of an appropriate counting method"
    - "a review of the literature on citation impact indicators"
    - "network analysis of zentralblatt math data"
    - "the leiden ranking 2011 2012 data collection indicators and interpretation"

Connected through hyperedge HE-5 (induced by source paper "a conservation rule for constructing bibliometric network matrices"):
  with members:
    - "constructing bibliometric networks a comparison between full and fractional counting"
    - "the normalization of co authorship networks in the bibliometric evaluation the government stimulation programs of china and korea"

Connected through hyperedge HE-6 (induced by source paper "an algebraic approach to temporal network analysis based on temporal quantities"):
  with members:
    - "semirings for temporal network analysis"
    - "time varying graphs and dynamic networks"

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)