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 "towards building a multilingual sememe knowledge base predicting sememes for babelnet synsets"):
  Abstract: A sememe is defined as the minimum semantic unit of human languages. Sememe knowledge bases (KBs), which contain words annotated with sememes, have been successfully applied to many NLP tasks. However, existing sememe KBs are built on only a few languages, which hinders their widespread utilization. To address the issue, we propose to build a unified sememe KB for multiple languages based on BabelNet, a multilingual encyclopedic dictionary. We first build a dataset serving as the seed of the multilingual sememe KB. It manually annotates sememes for over $15$ thousand synsets (the entries of BabelNet). Then, we present a novel task of automatic sememe prediction for synsets, aiming to expand the seed dataset into a usable KB. We also propose two simple and effective models, which exploit different information of synsets. Finally, we conduct quantitative and qualitative analyses to explore important factors and difficulties in the task. All the source code and data of this work can be obtained on this https URL.

Includes members:
  Member "multi channel reverse dictionary model":
    also connected through other hyperedges:
      (none)
  Member "enhancing recurrent neural networks with sememes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi channel reverse dictionary model")
  Member "modeling semantic compositionality with sememe knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi channel reverse dictionary model")
  Member "open the boxes of words incorporating sememes into textual adversarial attack":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi channel reverse dictionary model")
  Member "openhownet an open sememe based lexical knowledge base":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi channel reverse dictionary model")
  Member "incorporating chinese characters of words for lexical sememe prediction":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "lexical sememe prediction using dictionary definitions by capturing local semantic correspondence")
  Member "language modeling with sparse product of sememe experts":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "lexical sememe prediction using dictionary definitions by capturing local semantic correspondence")
  Member "a novel embedding model for knowledge base completion based on convolutional neural network":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a benchmarking study of embedding based entity alignment for knowledge graphs")

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)