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 "mining entity synonyms with efficient neural set generation"):
  Abstract: Mining entity synonym sets (i.e., sets of terms referring to the same entity) is an important task for many entity-leveraging applications. Previous work either rank terms based on their similarity to a given query term, or treats the problem as a two-phase task (i.e., detecting synonymy pairs, followed by organizing these pairs into synonym sets). However, these approaches fail to model the holistic semantics of a set and suffer from the error propagation issue. Here we propose a new framework, named SynSetMine, that efficiently generates entity synonym sets from a given vocabulary, using example sets from external knowledge bases as distant supervision. SynSetMine consists of two novel modules: (1) a set-instance classifier that jointly learns how to represent a permutation invariant synonym set and whether to include a new instance (i.e., a term) into the set, and (2) a set generation algorithm that enumerates the vocabulary only once and applies the learned set-instance classifier to detect all entity synonym sets in it. Experiments on three real datasets from different domains demonstrate both effectiveness and efficiency of SynSetMine for mining entity synonym sets.

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 "entity set search of scientific literature an unsupervised ranking approach":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "discovering hypernymy in text rich heterogeneous information network by exploiting context granularity")
  Member "deep sets":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "stochastic latent residual video prediction")
  Member "automatic synonym discovery with knowledge bases":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "place deduplication with embeddings")
  Member "fighting with the sparsity of synonymy dictionaries for automatic synset induction":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "watset local global graph clustering with applications in sense and frame induction")
  Member "learning to cluster in order to transfer across domains and tasks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "m adda unsupervised domain adaptation with deep metric learning")
  Member "watset automatic induction of synsets from a graph of synonyms":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "place deduplication with embeddings")
  Member "solving verbal comprehension questions in iq test by knowledge powered word embedding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "automatic synonym discovery with knowledge bases")

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)