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: "weighted indices for evaluating the quality of research with multiple authorship"
  Abstract: Devising an index to measure the quality of research is a challenging task. In this paper, we propose a set of indices to evaluate the quality of research produced by an author. Our indices utilize a policy that assigns the weights to multiple authors of a paper. We have considered two weight assignment policies: positionally weighted and equally weighted. We propose two classes of weighted indices: weighted h-indices and weighted citation h-cuts. Further, we compare our weighted h-indices with the original h-index for a selected set of authors. As opposed to h-index, our weighted h-indices take into account the weighted contributions of individual authors in multi-authored papers, and may serve as an improvement over h-index. The other class of weighted indices that we call weighted citation h-cuts take into account the number of citations that are in excess of those required to compute the index, and may serve as a supplement to h-index or its variants.

Connected through hyperedge HE-1 (induced by source paper "h index and its alternative a review"):
  with members:
    - "restricting the h index to a publication and citation time window a case study of a timed hirsch index"
    - "a variant of the h index to measure recent performance"
    - "a review of the characteristics of 108 author level bibliometric indicators"
    - "impact vitality a measure for excellent scientists"
    - "socializing the h index"
    - "simple arithmetic versus intuitive understanding the case of the impact factor"
    - "central indexes to the citation distribution a complement to the h index"
    - "the inconsistency of the h index"

Connected through hyperedge HE-2 (induced by source paper "a review of the literature on citation impact indicators"):
  with members:
    - "a sensitivity analysis of researchers productivity rankings to the time of citation observation"
    - "the precision of the arithmetic mean geometric mean and percentiles for citation data an experimental simulation modelling approach"
    - "the journal coverage of web of science and scopus a comparative analysis"
    - "measuring academic influence not all citations are equal"
    - "a review of theory and practice in scientometrics"
    - "comprehensive indicator comparisons intelligible to non experts the case of two snip versions"
    - "methods for estimating the size of google scholar"
    - "large scale analysis of the accuracy of the journal classification systems of web of science and scopus"

Connected through hyperedge HE-3 (induced by source paper "polynomial weights or generalized geometric weights yet another scheme for assigning credits to multiple authors"):
  with members:
    - "resequencing a method for conforming to conventions for sharing credits among multiple authors"
    - "generalized linear weights for sharing credits among multiple authors"

Connected through hyperedge HE-4 (induced by source paper "resequencing a method for conforming to conventions for sharing credits among multiple authors"):
  with members:
    - "generalized linear weights for sharing credits among multiple authors"

Connected through hyperedge HE-5 (induced by source paper "generalized linear weights for sharing credits among multiple authors"):
  with members:
    - "analysis of generalized impact factor and indices of journals"

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.IR(Information Retrieval)