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: "query tracking for e commerce conversational search a machine comprehension perspective"
  Abstract: With the development of dialog techniques, conversational search has attracted more and more attention as it enables users to interact with the search engine in a natural and efficient manner. However, comparing with the natural language understanding in traditional task-oriented dialog which focuses on slot filling and tracking, the query understanding in E-commerce conversational search is quite different and more challenging due to more diverse user expressions and complex intentions. In this work, we define the real-world problem of query tracking in E-commerce conversational search, in which the goal is to update the internal query after each round of interaction. We also propose a self attention based neural network to handle the task in a machine comprehension perspective. Further more we build a novel E-commerce query tracking dataset from an operational E-commerce Search Engine, and experimental results on this dataset suggest that our proposed model outperforms several baseline methods by a substantial gain for Exact Match accuracy and F1 score, showing the potential of machine comprehension like model for this task.

Connected through hyperedge HE-1 (induced by source paper "dynamic search optimizing the game of information seeking"):
  with members:
    - "multi step retriever reader interaction for scalable open domain question answering"
    - "an algorithmic perspective on imitation learning"
    - "a reinforcement learning driven translation model for search oriented conversational systems"
    - "neural approaches to conversational ai"
    - "top k off policy correction for a reinforce recommender system"
    - "a click sequence model for web search"
    - "response ranking with deep matching networks and external knowledge in information seeking conversation systems"
    - "attentive memory networks efficient machine reading for conversational search"

Connected through hyperedge HE-2 (induced by source paper "exact k recommendation via maximal clique optimization"):
  with members:
    - "a multi task selected learning approach for solving 3d flexible bin packing problem"
    - "learning a deep listwise context model for ranking refinement"
    - "automatic generation of chinese short product titles for mobile display"
    - "representing verbs as argument concepts"
    - "a brand level ranking system with the customized attention gru model"
    - "deep cascade multi task learning for slot filling in online shopping assistant"
    - "behavioral cloning from observation"
    - "attention is all you need"

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)