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: "manipulating google scholar citations and google scholar metrics simple easy and tempting"
  Abstract: The launch of Google Scholar Citations and Google Scholar Metrics may provoke a revolution in the research evaluation field as it places within every researchers reach tools that allow bibliometric measuring. In order to alert the research community over how easily one can manipulate the data and bibliometric indicators offered by Google s products we present an experiment in which we manipulate the Google Citations profiles of a research group through the creation of false documents that cite their documents, and consequently, the journals in which they have published modifying their H index. For this purpose we created six documents authored by a faked author and we uploaded them to a researcher s personal website under the University of Granadas domain. The result of the experiment meant an increase of 774 citations in 129 papers (six citations per paper) increasing the authors and journals H index. We analyse the malicious effect this type of practices can cause to Google Scholar Citations and Google Scholar Metrics. Finally, we conclude with several deliberations over the effects these malpractices may have and the lack of control tools these tools offer

Connected through hyperedge HE-1 (induced by source paper "implementing recommendation algorithms in a large scale biomedical science knowledge base"):
  with members:
    - "google scholar metrics 2014 a low cost bibliometric tool"

Connected through hyperedge HE-2 (induced by source paper "how well developed are altmetrics a cross disciplinary analysis of the presence of alternative metrics in scientific publications"):
  with members:
    - "tracing scientist s research trends realtimely"
    - "is there currently a scientific revolution in scientometrics"
    - "coverage and adoption of altmetrics sources in the bibliometric community"
    - "how the scientific community reacts to newly submitted preprints article downloads twitter mentions and citations"
    - "the validation of advanced bibliometric indicators through peer assessments a comparative study using data from incites and f1000"
    - "beyond citations scholars visibility on the social web"
    - "altmetrics in the wild using social media to explore scholarly impact"
    - "towards a new crown indicator some theoretical considerations"

Connected through hyperedge HE-3 (induced by source paper "h index communication journals according to google scholar metrics 2008 2012"):
  with members:
    - "h index of scientific nursing journals according to google scholar metrics 2007 2011"
    - "ranking journals could google scholar metrics be an alternative to journal citation reports and scimago journal rank"

Connected through hyperedge HE-4 (induced by source paper "ranking journals could google scholar metrics be an alternative to journal citation reports and scimago journal rank"):
  with members:
    - "a principal component analysis of 39 scientific impact measures"
    - "ranking forestry journals using the h index"

Connected through hyperedge HE-5 (induced by source paper "the google scholar experiment how to index false papers and manipulate bibliometric indicators"):
  with members:
    - "ranking journals could google scholar metrics be an alternative to journal citation reports and scimago journal rank"
    - "the inconsistency of the h index"

Connected through hyperedge HE-6 (induced by source paper "h index of scientific nursing journals according to google scholar metrics 2007 2011"):
  with members:
    - "ranking journals could google scholar metrics be an alternative to journal citation reports and scimago journal rank"

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)