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 "the coverage of microsoft academic analyzing the publication output of a university"):
  Abstract: Abstract This is the first detailed study on the coverage of Microsoft Academic (MA). Based on the complete and verified publication list of a university, the coverage of MA was assessed and compared with two benchmark databases, Scopus and Web of Science (WoS), on the level of individual publications. Citation counts were analyzed, and issues related to data retrieval and data quality were examined. A Perl script was written to retrieve metadata from MA based on publication titles. The script is freely available on GitHub. We find that MA covers journal articles, working papers, and conference items to a substantial extent and indexes more document types than the benchmark databases (e.g., working papers, dissertations). MA clearly surpasses Scopus and WoS in covering book-related document types and conference items but falls slightly behind Scopus in journal articles. The coverage of MA is favorable for evaluative bibliometrics in most research fields, including economics/business, computer/information sciences, and mathematics. However, MA shows biases similar to Scopus and WoS with regard to the coverage of the humanities, non-English publications, and open-access publications. Rank correlations of citation counts are high between MA and the benchmark databases. We find that the publication year is correct for 89.5% of all publications and the number of authors is correct for 95.1% of the journal articles. Given the fast and ongoing development of MA, we conclude that MA is on the verge of becoming a bibliometric superpower. However, comprehensive studies on the quality of MA metadata are still lacking.

Includes members:
  Member "leveraging citation networks to visualize scholarly influence over time":
    also connected through other hyperedges:
      (none)
  Member "citation analysis with microsoft academic":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "influence flowers of academic entities")
  Member "semantometrics towards fulltext based research evaluation":
    also connected through other hyperedges:
      (none)
  Member "quantifying the diaspora of knowledge in the last century":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "citation analysis with microsoft academic")
  Member "ranking academic institutions on potential paper acceptance in upcoming conferences":
    also connected through other hyperedges:
      (none)
  Member "ensemble enabled weighted pagerank":
    also connected through other hyperedges:
      (none)
  Member "simplified relative citation ratio for static paper ranking ufmg latin at wsdm cup 2016":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "citation analysis with microsoft academic")
  Member "predicting the future relevance of research institutions the winning solution of the kdd cup 2016":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "locally constant networks")

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)