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: "what can heterogeneity add to the scientometric map steps towards algorithmic historiography"
  Abstract: The Actor Network represents heterogeneous entities as actants (Callon et al., 1983; 1986). Although computer programs for the visualization of social networks increasingly allow us to represent heterogeneity in a network using different shapes and colors for the visualization, hitherto this possibility has scarcely been exploited (Mogoutov et al., 2008). In this contribution to the Festschrift, I study the question of what heterogeneity can add specifically to the visualization of a network. How does an integrated network improve on the one-dimensional ones (such as co-word and co-author maps)? The oeuvre of Michel Callon is used as the case materials, that is, his 65 papers which can be retrieved from the (Social) Science Citation Index since 1975.

Connected through hyperedge HE-1 (induced by source paper "referenced publication year spectroscopy rpys and algorithmic historiography the bibliometric reconstruction of andras schubert s œuvre"):
  with members:
    - "citnetexplorer a new software tool for analyzing and visualizing citation networks"
    - "detecting the historical roots of research fields by reference publication year spectroscopy rpys"
    - "referenced publication years spectroscopy applied to imetrics scientometrics journal of informetrics and a relevant subset of jasist"
    - "interdisciplinarity at the journal and specialty level the changing knowledge bases of the journal cognitive science"

Connected through hyperedge HE-2 (induced by source paper "innovation as a nonlinear process the scientometric perspective and the specification of an innovation opportunities explorer"):
  with members:
    - "the knowledge based economy and the triple helix model"
    - "how to create an innovation accelerator"
    - "mapping excellence in the geography of science an approach based on scopus data"
    - "interactive overlays a new method for generating global journal maps from web of science data"
    - "which cities produce excellent papers worldwide more than can be expected a new mapping approach using google maps based on statistical significance testing"
    - "mapping the geography of science distribution patterns and networks of relations among cities and institutes"
    - "science overlay maps a new tool for research policy and library management"

Connected through hyperedge HE-3 (induced by source paper "visualization and analysis of frames in collections of messages content analysis and the measurement of meaning"):
  with members:
    - "the semantic mapping of words and co words in contexts"
    - "a comparison of two techniques for bibliometric mapping multidimensional scaling and vos"
    - "the communication of meaning and the structuration of expectations giddens structuration theory and luhmann s self organization"
    - "co occurrence matrices and their applications in information science extending aca to the web environment"

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.DL(Digital Libraries)