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 "vulnds top k vulnerable sme detection system in networked loans"):
  Abstract: Groups of small and medium enterprises (SMEs) can back each other to obtain loans from banks and thus form guarantee networks. If the loan repayment of a small business in the network defaults, its backers are required to repay the loan. Therefore, risk over networked enterprises may cause significant contagious damage. In real-world applications, it is critical to detect top vulnerable nodes in such complex financial network with near real-time performance. To address this challenge, we introduce VulnDS: a top-k vulnerable SME detection system for large-scale financial networks, which is deployed in our collaborated bank. First, we model the risks of the guaranteed-loan network by a probabilistic graph, which consists of the guarantee-loan network structure, self-risks for the nodes, and diffusion probability for the edges. Then, we propose a sampling-based approach with a tight theoretical guarantee. To scale for large networks, novel optimization techniques are developed. We conduct extensive experiments on three financial datasets, in addition with 5 large-scale benchmark networks. The evaluation results show that the proposed method can achieve over 10-100x speedup ratio compared with baseline methods.

Includes members:
  Member "an in depth comparison of s t reliability algorithms over uncertain graphs":
    also connected through other hyperedges:
      (none)
  Member "joint deep modeling of users and items using reviews for recommendation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "chameleon a deep learning meta architecture for news recommender systems phd thesis")
  Member "wide deep learning for recommender systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "chameleon a deep learning meta architecture for news recommender systems phd thesis")
  Member "the lifecycle and cascade of wechat social messaging groups":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deepinf social influence prediction with deep learning")

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.CE(Computational Engineering, Finance, and Science)