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 "hierarchical gating networks for sequential recommendation"):
  Abstract: The chronological order of user-item interactions is a key feature in many recommender systems, where the items that users will interact may largely depend on those items that users just accessed recently. However, with the tremendous increase of users and items, sequential recommender systems still face several challenging problems: (1) the hardness of modeling the long-term user interests from sparse implicit feedback; (2) the difficulty of capturing the short-term user interests given several items the user just accessed. To cope with these challenges, we propose a hierarchical gating network (HGN), integrated with the Bayesian Personalized Ranking (BPR) to capture both the long-term and short-term user interests. Our HGN consists of a feature gating module, an instance gating module, and an item-item product module. In particular, our feature gating and instance gating modules select what item features can be passed to the downstream layers from the feature and instance levels, respectively. Our item-item product module explicitly captures the item relations between the items that users accessed in the past and those items users will access in the future. We extensively evaluate our model with several state-of-the-art methods and different validation metrics on five real-world datasets. The experimental results demonstrate the effectiveness of our model on Top-N sequential recommendation.

Includes members:
  Member "signed distance based deep memory recommender":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "adversarial mahalanobis distance based attentive song recommender for automatic playlist continuation")
  Member "regularizing matrix factorization with user and item embeddings for recommendation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adversarial mahalanobis distance based attentive song recommender for automatic playlist continuation")
  Member "gated attentive autoencoder for content aware recommendation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "adversarial mahalanobis distance based attentive song recommender for automatic playlist continuation")
  Member "xdeepfm combining explicit and implicit feature interactions for recommender systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cross gcn enhancing graph convolutional network with k order feature interactions")
  Member "point of interest recommendation exploiting self attentive autoencoders with neighbor aware influence":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "adversarial mahalanobis distance based attentive song recommender for automatic playlist continuation")
  Member "a simple convolutional generative network for next item recommendation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "parameter efficient transfer from sequential behaviors for user profiling and recommendation")
  Member "recurrent neural networks with top k gains for session based recommendations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "chameleon a deep learning meta architecture for news recommender systems phd thesis")
  Member "personalized top n sequential recommendation via convolutional sequence embedding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "advances in collaborative filtering and ranking")

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.IR(Information Retrieval)