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 "inducing hypernym relationships based on order theory"):
  Abstract: This paper introduces Strict Partial Order Networks (SPON), a novel neural network architecture designed to enforce asymmetry and transitive properties as soft constraints. We apply it to induce hypernymy relations by training with is-a pairs. We also present an augmented variant of SPON that can generalize type information learned for in-vocabulary terms to previously unseen ones. An extensive evaluation over eleven benchmarks across different tasks shows that SPON consistently either outperforms or attains the state of the art on all but one of these benchmarks.

Includes members:
  Member "inferring concept hierarchies from text corpora via hyperbolic embeddings":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "keml a knowledge enriched meta learning framework for lexical relation classification")
  Member "hearst patterns revisited automatic hypernym detection from large text corpora":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "keml a knowledge enriched meta learning framework for lexical relation classification")
  Member "hierarchical density order embeddings":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "query2box reasoning over knowledge graphs in vector space using box embeddings")
  Member "poincar e embeddings for learning hierarchical representations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the tensor brain semantic decoding for perception and memory")
  Member "improved representation learning for predicting commonsense ontologies":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "query2box reasoning over knowledge graphs in vector space using box embeddings")
  Member "relations such as hypernymy identifying and exploiting hearst patterns in distributional vectors for lexical entailment":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "keml a knowledge enriched meta learning framework for lexical relation classification")
  Member "hypernyms under siege linguistically motivated artillery for hypernymy detection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the polar framework polar opposites enable interpretability of pre trained word embeddings")
  Member "improving hypernymy detection with an integrated path based and distributional method":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "keml a knowledge enriched meta learning framework for lexical relation classification")

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.AI(Artificial Intelligence)