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: "optimal multi paragraph text segmentation by dynamic programming"
  Abstract: There exist several methods of calculating a similarity curve, or a sequence of similarity values, representing the lexical cohesion of successive text constituents, e.g., paragraphs. Methods for deciding the locations of fragment boundaries are, however, scarce. We propose a fragmentation method based on dynamic programming. The method is theoretically sound and guaranteed to provide an optimal splitting on the basis of a similarity curve, a preferred fragment length, and a cost function defined. The method is especially useful when control on fragment size is of importance.

Connected through hyperedge HE-1 (induced by source paper "text segmentation using named entity recognition and co reference resolution in english and greek texts"):
  with members:
    - "a comparison of named entity recognition tools applied to biographical texts"
    - "advances in domain independent linear text segmentation"

Connected through hyperedge HE-2 (induced by source paper "a dynamic programming algorithm for the segmentation of greek texts"):
  with members:
    - "advances in domain independent linear text segmentation"
    - "linear segmentation and segment significance"

Connected through hyperedge HE-3 (induced by source paper "advances in domain independent linear text segmentation"):
  with members:
    - "linear segmentation and segment significance"

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)