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 "large scale analysis of the accuracy of the journal classification systems of web of science and scopus"):
  Abstract: Journal classification systems play an important role in bibliometric analyses. The two most important bibliographic databases, Web of Science and Scopus, each provide a journal classification system. However, no study has systematically investigated the accuracy of these classification systems. To examine and compare the accuracy of journal classification systems, we define two criteria on the basis of direct citation relations between journals and categories. We use Criterion I to select journals that have weak connections with their assigned categories, and we use Criterion II to identify journals that are not assigned to categories with which they have strong connections. If a journal satisfies either of the two criteria, we conclude that its assignment to categories may be questionable. Accordingly, we identify all journals with questionable classifications in Web of Science and Scopus. Furthermore, we perform a more in-depth analysis for the field of Library and Information Science to assess whether our proposed criteria are appropriate and whether they yield meaningful results. It turns out that according to our citation-based criteria Web of Science performs significantly better than Scopus in terms of the accuracy of its journal classification system.

Includes members:
  Member "which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "practical method to reclassify web of science articles into unique subject categories and broad disciplines")
  Member "the journal coverage of web of science and scopus a comparative analysis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a tale of two databases the use of web of science and scopus in academic papers")
  Member "a review of the literature on citation impact indicators":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data")
  Member "the operationalization of fields as wos subject categories wcs in evaluative bibliometrics the cases of library and information science and science technology studies":
    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 "citation analysis may severely underestimate the impact of clinical research as compared to basic research":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "should citations be field normalized in evaluative bibliometrics an empirical analysis based on propensity score matching")
  Member "a new methodology for constructing a publication level classification system of science":
    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 "comparing bibliometric statistics obtained from the web of science and scopus":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "readership data and research impact")

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)