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 "exchange based diffusion in hb graphs highlighting complex relationships"):
  Abstract: Most networks tend to show complex and multiple relationships between entities. Networks are usually modeled by graphs or hypergraphs; nonetheless a given entity can occur many times in a relationship: this brings the need to deal with multisets instead of sets or simple edges. Diffusion processes are useful to highlight interesting parts of a network: they usually start with a stroke at one vertex and diffuse throughout the network to reach a uniform distribution. Several iterations of the process are required prior to reaching a stable solution. We propose an alternative solution to highlighting main components of a network using a diffusion process based on exchanges; it is an iterative two-phase step exchange process. This process allows to evaluate the importance not only at the vertices level but also at the regrouping level. To model the diffusion process, we extend the concept of hypergraphs that are family of sets to family of multisets, that we call hb-graphs.

Includes members:
  Member "adjacency and tensor representation in general hypergraphs part 2 multisets hb graphs and related e adjacency tensors":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "tuning ranking in co occurrence networks with general biased exchange based diffusion on hyper bag graphs")
  Member "bag of words as target for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "paraphrase generation with latent bag of words")
  Member "identifying mild traumatic brain injury patients from mr images using bag of visual words":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mtbi identification from diffusion mr images using bag of adversarial visual features")
  Member "hypergraph covering problems motivated by genome assembly questions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "hypergraphs an introduction and review")

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.DS(Data Structures and Algorithms)