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: "initial comparison of linguistic networks measures for parallel texts"
  Abstract: This paper presents preliminary results of Croatian syllable networks analysis. Syllable network is a network in which nodes are syllables and links between them are constructed according to their connections within words. In this paper we analyze networks of syllables generated from texts collected from the Croatian Wikipedia and Blogs. As a main tool we use complex network analysis methods which provide mechanisms that can reveal new patterns in a language structure. We aim to show that syllable networks have much higher clustering coefficient in comparison to Erd\"os-Renyi random networks. The results indicate that Croatian syllable networks exhibit certain properties of a small world networks. Furthermore, we compared Croatian syllable networks with Portuguese and Chinese syllable networks and we showed that they have similar properties.

Connected through hyperedge HE-1 (induced by source paper "comparison of the language networks from literature and blogs"):
  with members:
    - "a preliminary study of croatian language syllable networks"
    - "preliminary report on the structure of croatian linguistic co occurrence networks"

Connected through hyperedge HE-2 (induced by source paper "complex networks measures for differentiation between normal and shuffled croatian texts"):
  with members:
    - "preliminary report on the structure of croatian linguistic co occurrence networks"
    - "the effect of linguistic constraints on the large scale organization of language"

Connected through hyperedge HE-3 (induced by source paper "network motifs analysis of croatian literature"):
  with members:
    - "complex networks measures for differentiation between normal and shuffled croatian texts"

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)