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: "a comparison between two main academic literature collections web of science and scopus databases"
  Abstract: Nowadays, the world’s scientific community has been publishing an enormous number of papers in different scientific fields. In such environment, it is essential to know which databases are equally efficient and objective for literature searches. It seems that two most extensive databases are Web of Science and Scopus. Besides searching the literature, these two databases used to rank journals in terms of their productivity and the total citations received to indicate the journals impact, prestige or influence. This article attempts to provide a comprehensive comparison of these databases to answer frequent questions which researchers ask, such as: How Web of Science and Scopus are different? In which aspects these two databases are similar? Or, if the researchers are forced to choose one of them, which one should they prefer? For answering these questions, these two databases will be compared based on their qualitative and quantitative characteristics.

Connected through hyperedge HE-1 (induced by source paper "knowledge management strategies and processes in agile software development a systematic literature review"):
  with members:
    - "knowledge management in software engineering a systematic review of studied concepts findings and research methods used"

Connected through hyperedge HE-2 (induced by source paper "a natural language interface to a graph based bibliographic information retrieval system"):
  with members:
    - "analysis of named entity recognition and linking for tweets"

Connected through hyperedge HE-3 (induced by source paper "national research impact indicators from mendeley readers"):
  with members:
    - "the vqr italy s second national research assessment methodological failures and ranking distortions"
    - "cited half life of the journal literature"
    - "field normalized citation impact indicators and the choice of an appropriate counting method"
    - "tweets vs mendeley readers how do these two social media metrics differ"
    - "do altmetrics correlate with citations extensive comparison of altmetric indicators with citations from a multidisciplinary perspective"
    - "tweets as impact indicators examining the implications of automated bot accounts on twitter"
    - "how well developed are altmetrics a cross disciplinary analysis of the presence of alternative metrics in scientific publications"
    - "the leiden ranking 2011 2012 data collection indicators and interpretation"

Connected through hyperedge HE-4 (induced by source paper "power laws in citation distributions evidence from scopus"):
  with members:
    - "tsallis q exponential describes the distribution of scientific citations a new characterization of the impact"

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)