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: "role of interdisciplinarity in computer sciences quantification impact and life trajectory"
  Abstract: The tremendous advances in computer science in the last few decades have provided the platform to address and solve complex problems using interdisciplinary research. In this paper, we investigate how the extent of interdisciplinarity in computer science domain (which is further divided into 24 research fields) has changed over the last 50 years. To this end, we collect a massive bibliographic dataset with rich metadata information. We start with quantifying interdisciplinarity of a field in terms of the diversity of topics and citations. We then analyze the effect of interdisciplinary research on the scientific impact of individual fields and observe that highly disciplinary and highly interdisciplinary papers in general have a low scientific impact; remarkably those that are able to strike a balance between the two extremes eventually land up having the highest impact. Further, we study the reciprocity among fields through citation interactions and notice that links from one field to related and citation-intensive fields (fields producing large number of citations) are reciprocated heavily. A systematic analysis of the citation interactions reveals the life trajectory of a research field, which generally undergoes three phases -- a growing phase, a matured phase and an interdisciplinary phase. The combination of metrics and empirical observations presented here provides general benchmarks for future studies of interdisciplinary research activities in other domains of science.

Connected through hyperedge HE-1 (induced by source paper "mendeley reader counts for us computer science conference papers and journal articles"):
  with members:
    - "google scholar web of science and scopus a systematic comparison of citations in 252 subject categories"
    - "on the relationships between bibliographic characteristics of scientific documents and citation and mendeley readership counts a large scale analysis of web of science publications"
    - "could scientists use altmetric com scores to predict longer term citation counts"
    - "which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge"
    - "mendeley readership as a filtering tool to identify highly cited publications"
    - "are the discretised lognormal and hooked power law distributions plausible for citation data"
    - "more precise methods for national research citation impact comparisons"
    - "tweets vs mendeley readers how do these two social media metrics differ"

Connected through hyperedge HE-2 (induced by source paper "viewing computer science through citation analysis salton and bergmark redux"):
  with members:
    - "from louvain to leiden guaranteeing well connected communities"
    - "which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge"
    - "parallel local graph clustering"
    - "clustering scientific publications based on citation relations a systematic comparison of different methods"
    - "analysis of network clustering algorithms and cluster quality metrics at scale"
    - "large scale analysis of the accuracy of the journal classification systems of web of science and scopus"
    - "a new methodology for constructing a publication level classification system of science"

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)