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: "categorization of comparative sentences for argument mining"
  Abstract: We present the first work on domain-independent comparative argument mining (CAM), which is the automatic extraction of direct comparisons from text. After motivating the need and identifying the widespread use of this so far under-researched topic, we present the first publicly available open-domain dataset for CAM. The dataset was collected using crowdsourcing and contains 7199 unique sentences for 217 distinct comparison target pairs selected over several domains, of which 27% contain a directed (better vs. worse) comparison. In classification experiments, we examine the impact of representations, features, and classifiers, and reach an F1-score of 88% with a gradient boosting model based on pre-trained sentence embeddings, especially reliably identifying non-comparative sentences. This paves the way for domain-independent comparison extraction from web-scale corpora for the use in result ranking and presentation for comparative queries.

Connected through hyperedge HE-1 (induced by source paper "answering comparative questions better than ten blue links"):
  with members:
    - "building a web scale dependency parsed corpus from commoncrawl"
    - "what is the essence of a claim cross domain claim identification"
    - "social media argumentation mining the quest for deliberateness in raucousness"
    - "understanding and detecting supporting arguments of diverse types"
    - "xgboost a scalable tree boosting system"

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.CL(Computation and Language)