human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "combining textual content and structure to improve dialog similarity"):
  Abstract: Chatbots, taking advantage of the success of the messaging apps and recent advances in Artificial Intelligence, have become very popular, from helping business to improve customer services to chatting to users for the sake of conversation and engagement (celebrity or personal bots). However, developing and improving a chatbot requires understanding their data generated by its users. Dialog data has a different nature of a simple question and answering interaction, in which context and temporal properties (turn order) creates a different understanding of such data. In this paper, we propose a novelty metric to compute dialogs' similarity based not only on the text content but also on the information related to the dialog structure. Our experimental results performed over the Switchboard dataset show that using evidence from both textual content and the dialog structure leads to more accurate results than using each measure in isolation.

Includes members:
  Member "how not to evaluate your dialogue system an empirical study of unsupervised evaluation metrics for dialogue response generation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "non autoregressive neural dialogue generation")
  Member "multiresolution recurrent neural networks an application to dialogue response generation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "avgout a simple output probability measure to eliminate dull responses")
  Member "learning end to end goal oriented dialog":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "the ubuntu dialogue corpus a large dataset for research in unstructured multi turn dialogue systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "toward interpretability of dual encoder models for dialogue response suggestions")
  Member "chameleons in imagined conversations a new approach to understanding coordination of linguistic style in dialogs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "ten social dimensions of conversations and relationships")

Question: Please tell me which class the source paper 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)