human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "a principled methodology for comparing relatedness measures for clustering publications"):
  Abstract: There are many different relatedness measures, based for instance on citation relations or textual similarity, that can be used to cluster scientific publications. We propose a principled methodology for evaluating the accuracy of clustering solutions obtained using these relatedness measures. We formally show that the proposed methodology has an important consistency property. The empirical analyses that we present are based on publications in the fields of cell biology, condensed matter physics, and economics. Using the BM25 text-based relatedness measure as evaluation criterion, we find that bibliographic coupling relations yield more accurate clustering solutions than direct citation relations and co-citation relations. The so-called extended direct citation approach performs similarly to or slightly better than bibliographic coupling in terms of the accuracy of the resulting clustering solutions. The other way around, using a citation-based relatedness measure as evaluation criterion, BM25 turns out to yield more accurate clustering solutions than other text-based relatedness measures.

Includes members:
  Member "from louvain to leiden guaranteeing well connected communities":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "shapevis high dimensional data visualization at scale")
  Member "granularity of algorithmically constructed publication level classifications of research publications identification of topics":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "practical method to reclassify web of science articles into unique subject categories and broad disciplines")
  Member "algorithmically generated subject categories based on citation relations an empirical micro study using papers on overall water splitting":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "practical method to reclassify web of science articles into unique subject categories and broad disciplines")
  Member "which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "practical method to reclassify web of science articles into unique subject categories and broad disciplines")
  Member "constructing bibliometric networks a comparison between full and fractional counting":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "who pays comparing cost sharing models for a gold open access publication environment")
  Member "clustering scientific publications based on citation relations a systematic comparison of different methods":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "practical method to reclassify web of science articles into unique subject categories and broad disciplines")
  Member "citnetexplorer a new software tool for analyzing and visualizing citation networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "discovering seminal works with marker papers")
  Member "a new methodology for constructing a publication level classification system of science":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "practical method to reclassify web of science articles into unique subject categories and broad disciplines")

Question: Please tell me which class the source paper 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)