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 "primal meaning recommendation for chinese words and phrases via descriptions in on line encyclopedia"):
  Abstract: Polysemy is a very common phenomenon in modern languages. Most of previous work treat the multiple meanings of a word equally. However, under many circumstances, there exists a primal meaning for the word. Many of the new appearing meanings of the words are either originated from a primal meaning, or are merely literal references to the original word, e.g., apple (fruit), Apple (Inc), and Apple (movie). When constructing knowledge base from on-line encyclopedia data, it would be more efficient to be aware of the information about the importance of the senses. In this paper, we would like to explore a way to automatically recommend the primal meaning of a word based on the textual descriptions of the multiple meanings of a word from online encyclopedia websites. We propose a hybrid model that captures both the pattern of the description and the relationship between different descriptions with both distantly supervised and unsupervised models. The experiment results show that our method yields very good result with a p@1 score of 80.6%, and a MAP of 89.0%, surpassing the Word-Sum baseline by a big margin (P@1 is 62.7% and MAP is 76.8%).

Includes members:
  Member "exploration on generating traditional chinese medicine prescription from symptoms with an end to end method":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "syndrome aware herb recommendation with multi graph convolution network")
  Member "embedding words and senses together via joint knowledge enhanced training":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "semantic relatedness for keyword disambiguation exploiting different embeddings")
  Member "skip thought vectors":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a survey on contextual embeddings")
  Member "sequence to sequence learning with neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "chameleon a deep learning meta architecture for news recommender systems phd thesis")
  Member "distributed representations of words and phrases and their compositionality":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")

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)