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: "reducing semantic complexity in distributed digital libraries treatment of term vagueness and document re ranking"
  Abstract: The purpose of the paper is to propose models to reduce the semantic complexity in heterogeneous DLs. The aim is to introduce value-added services (treatment of term vagueness and document re-ranking) that gain a certain quality in DLs if they are combined with heterogeneity components established in the project "Competence Center Modeling and Treatment of Semantic Heterogeneity". Empirical observations show that freely formulated user terms and terms from controlled vocabularies are often not the same or match just by coincidence. Therefore, a value-added service will be developed which rephrases the natural language searcher terms into suggestions from the controlled vocabulary, the Search Term Recommender (STR). Two methods, which are derived from scientometrics and network analysis, will be implemented with the objective to re-rank result sets by the following structural properties: the ranking of the results by core journals (so-called Bradfordizing) and ranking by centrality of authors in co-authorship networks.

Connected through hyperedge HE-1 (induced by source paper "editorial for the proceedings of the workshop knowledge maps and information retrieval kmir2014 at digital libraries 2014"):
  with members:
    - "mapping eins an exercise in mapping the network of excellence in internet science"

Connected through hyperedge HE-2 (induced by source paper "knowledge maps and information retrieval kmir"):
  with members:
    - "science models as value added services for scholarly information systems"

Connected through hyperedge HE-3 (induced by source paper "relevance distributions across bradford zones can bradfordizing improve search"):
  with members:
    - "science models as value added services for scholarly information systems"
    - "using lotkaian informetrics for ranking in digital libraries"
    - "applying science models for search"
    - "cross concordances terminology mapping and its effectiveness for information retrieval"

Connected through hyperedge HE-4 (induced by source paper "science models as value added services for scholarly information systems"):
  with members:
    - "applying centrality measures to impact analysis a coauthorship network analysis"
    - "implications of inter rater agreement on a student information retrieval evaluation"
    - "towards an explanatory and computational theory of scientific discovery"
    - "an evaluation of bradfordizing effects"
    - "building a terminology network for search"
    - "co authorship networks in the digital library research community"

Connected through hyperedge HE-5 (induced by source paper "applying science models for search"):
  with members:
    - "applying centrality measures to impact analysis a coauthorship network analysis"
    - "implications of inter rater agreement on a student information retrieval evaluation"
    - "towards an explanatory and computational theory of scientific discovery"
    - "co authorship networks in the digital library research community"

Connected through hyperedge HE-6 (induced by source paper "a science model driven retrieval prototype"):
  with members:
    - "science models as value added services for scholarly information systems"

Connected through hyperedge HE-7 (induced by source paper "building a terminology network for search"):
  with members:
    - "cross concordances terminology mapping and its effectiveness for information retrieval"
    - "treatment of semantic heterogeneity in information retrieval"

Connected through hyperedge HE-8 (induced by source paper "an evaluation of bradfordizing effects"):
  with members:
    - "cross concordances terminology mapping and its effectiveness for information retrieval"

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)