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: "understanding chatbot mediated task management"
  Abstract: Effective task management is essential to successful team collaboration. While the past decade has seen considerable innovation in systems that track and manage group tasks, these innovations have typically been outside of the principal communication channels: email, instant messenger, and group chat. Teams formulate, discuss, refine, assign, and track the progress of their collaborative tasks over electronic communication channels, yet they must leave these channels to update their task-tracking tools, creating a source of friction and inefficiency. To address this problem, we explore how bots might be used to mediate task management for individuals and teams. We deploy a prototype bot to eight different teams of information workers to help them create, assign, and keep track of tasks, all within their main communication channel. We derived seven insights for the design of future bots for coordinating work.

Connected through hyperedge HE-1 (induced by source paper "how should my chatbot interact a survey on human chatbot interaction design"):
  with members:
    - "from eliza to xiaoice challenges and opportunities with social chatbots"
    - "style transfer through back translation"
    - "personalizing dialogue agents i have a dog do you have pets too"
    - "can a chatbot determine my diet addressing challenges of chatbot application for meal recommendation"
    - "evaluating quality of chatbots and intelligent conversational agents"
    - "dailydialog a manually labelled multi turn dialogue dataset"
    - "a hybrid architecture for multi party conversational systems"
    - "chatbots greetings to human computer communication"

Connected through hyperedge HE-2 (induced by source paper "msrbot using bots to answer questions from software repositories"):
  with members:
    - "explainable software bot contributions case study of automated bug fixes"
    - "repairnator patches programs automatically"
    - "an additional set of automated eyes chatbots for agile retrospectives"
    - "how to design a program repair bot insights from the repairnator project"
    - "programming bots by synthesizing natural language expressions into api invocations"
    - "distributed representations of words and phrases and their compositionality"
    - "introduction to the conll 2003 shared task language independent named entity recognition"

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.HC(Human-Computer Interaction)