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 "hiexpan task guided taxonomy construction by hierarchical tree expansion"):
  Abstract: Taxonomies are of great value to many knowledge-rich applications. As the manual taxonomy curation costs enormous human effects, automatic taxonomy construction is in great demand. However, most existing automatic taxonomy construction methods can only build hypernymy taxonomies wherein each edge is limited to expressing the "is-a" relation. Such a restriction limits their applicability to more diverse real-world tasks where the parent-child may carry different relations. In this paper, we aim to construct a task-guided taxonomy from a domain-specific corpus and allow users to input a "seed" taxonomy, serving as the task guidance. We propose an expansion-based taxonomy construction framework, namely HiExpan, which automatically generates key term list from the corpus and iteratively grows the seed taxonomy. Specifically, HiExpan views all children under each taxonomy node forming a coherent set and builds the taxonomy by recursively expanding all these sets. Furthermore, HiExpan incorporates a weakly-supervised relation extraction module to extract the initial children of a newly-expanded node and adjusts the taxonomy tree by optimizing its global structure. Our experiments on three real datasets from different domains demonstrate the effectiveness of HiExpan for building task-guided taxonomies.

Includes members:
  Member "setexpan corpus based set expansion via context feature selection and rank ensemble":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "taxoexpan self supervised taxonomy expansion with position enhanced graph neural network")
  Member "end to end reinforcement learning for automatic taxonomy induction":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "taxoexpan self supervised taxonomy expansion with position enhanced graph neural network")
  Member "metapad meta pattern discovery from massive text corpora":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "taxoexpan self supervised taxonomy expansion with position enhanced graph neural network")
  Member "taxonomy induction using hypernym subsequences":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "taxoexpan self supervised taxonomy expansion with position enhanced graph neural network")
  Member "weakly supervised relation extraction by pattern enhanced embedding learning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "probabilistic logic neural networks for reasoning")
  Member "automated phrase mining from massive text corpora":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cube2net efficient query specific network construction with data cube organization")
  Member "pte predictive text embedding through large scale heterogeneous text networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "meta embeddings based on self attention")
  Member "line large scale information network embedding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "adversarial attacks and defenses on graphs a review and empirical study")

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)