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 "reciprocating preferences stablize matching college admissions revisited"):
  Abstract: In considering the college admissions problem, almost fifty years ago, Gale and Shapley came up with a simple abstraction based on preferences of students and colleges. They introduced the concept of stability and optimality; and proposed the deferred acceptance (DA) algorithm that is proven to lead to a stable and optimal solution. This algorithm is simple and computationally efficient. Furthermore, in subsequent studies it is shown that the DA algorithm is also strategy-proof, which means, when the algorithm is played out as a mechanism for matching two sides (e.g. colleges and students), the parties (colleges or students) have no incentives to act other than according to their true preferences. Yet, in practical college admission systems, the DA algorithm is often not adopted. Instead, an algorithm known as the Boston Mechanism (BM) or its variants are widely adopted. In BM, colleges accept students without deferral (considering other colleges' decisions), which is exactly the opposite of Gale-Shapley's DA algorithm. To explain and rationalize this reality, we introduce the notion of reciprocating preference to capture the influence of a student's interest on a college's decision. This model is inspired by the actual mechanism used to match students to universities in Hong Kong. The notion of reciprocating preference defines a class of matching algorithms, allowing different degrees of reciprocating preferences by the students and colleges. DA and BM are but two extreme cases (with zero and a hundred percent reciprocation) of this set. This model extends the notion of stability and optimality as well. As in Gale-Shapley's original paper, we discuss how the analogy can be carried over to the stable marriage problem, thus demonstrating the model's general applicability.

Includes members:
  Member "sponsored search market equilibria and the hungarian method":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the ad types problem")
  Member "social networks and stable matchings in the job market":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "graphical one sided markets")

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.GT(Computer Science and Game Theory)