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 "polynomial weights or generalized geometric weights yet another scheme for assigning credits to multiple authors"):
  Abstract: AbstractDevising a weight assignment policy for assigning credits to multipleauthorsofamanuscriptisachallengingtask. Inthispaper,wepresentaschemeforassigningcreditstomultipleauthorsthatwecallapolynomialweight assignment scheme. Wecompare our scheme with other schemesproposedintheliterature. Keywords: Polynomial weights, multiple authorship, credit assignment. 1 Introduction Assigning weights to multiple authors of a paper is a challenging task. Thechallenge comes from the fact that the conventions followed among diﬀerentareas of research are diﬀerent, and there is no universally agreed upon policyfor sharing credits of a multiauthored paper. The reason is that the conventionsfollowed among research groups might not depend only on the academic factors,sometimes, these conventionmight alsodepend onthe social, economic, regional,and scientiﬁc factors. Actually, a weight assignment scheme can only generateweights. How judiciously the scheme is applied is the responsibility of the onewho is evaluating the quality of research produced by an author or a set ofauthors. How the weights generated by a weight assignment policy can bemade in the conformance of the conventions followed by a research group ispartly described in [3]. We here focus on the schemes that generate weights(and not that are applied to a particular research ﬁeld).Many researchers focused on weight assignment schemes for sharing creditsamong multiple authors of a paper. Addressing multiple authorship mathemat-ically dates back to [4]. In [2], a weight assignment scheme called

Includes members:
  Member "resequencing a method for conforming to conventions for sharing credits among multiple authors":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "weighted indices for evaluating the quality of research with multiple authorship")
  Member "weighted indices for evaluating the quality of research with multiple authorship":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "h index and its alternative a review")
  Member "generalized linear weights for sharing credits among multiple authors":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "resequencing a method for conforming to conventions for sharing credits among multiple authors")

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)