human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "query reranking as a service"
  Abstract: The ranked retrieval model has rapidly become the de facto way for search query processing in client-server databases, especially those on the web. Despite of the extensive efforts in the database community on designing better ranking functions/mechanisms, many such databases in practice still fail to address the diverse and sometimes contradicting preferences of users on tuple ranking, perhaps (at least partially) due to the lack of expertise and/or motivation for the database owner to design truly effective ranking functions. This paper takes a different route on addressing the issue by defining a novel {\em query reranking problem}, i.e., we aim to design a third-party service that uses nothing but the public search interface of a client-server database to enable the on-the-fly processing of queries with any user-specified ranking functions (with or without selection conditions), no matter if the ranking function is supported by the database or not. We analyze the worst-case complexity of the problem and introduce a number of ideas, e.g., on-the-fly indexing, domination detection and virtual tuple pruning, to reduce the average-case cost of the query reranking algorithm. We also present extensive experimental results on real-world datasets, in both offline and live online systems, that demonstrate the effectiveness of our proposed techniques.

Connected through hyperedge HE-1 (induced by source paper "responsible scoring mechanisms through function sampling"):
  with members:
    - "rrr rank regret representative"
    - "on obtaining stable rankings"

Connected through hyperedge HE-2 (induced by source paper "on obtaining stable rankings"):
  with members:
    - "a nutritional label for rankings"
    - "qr2 a third party query reranking service over web databases"
    - "rrr rank regret representative"
    - "ranking with fairness constraints"
    - "discovering the skyline of web databases"
    - "crowdsourcing pareto optimal object finding by pairwise comparisons"
    - "optimal aggregation algorithms for middleware"

Connected through hyperedge HE-3 (induced by source paper "rrr rank regret representative"):
  with members:
    - "qr2 a third party query reranking service over web databases"
    - "efficient algorithms for k regret minimizing sets"
    - "discovering the skyline of web databases"
    - "crowdsourcing pareto optimal object finding by pairwise comparisons"
    - "on the expected complexity of random convex hulls"
    - "optimal aggregation algorithms for middleware"

Connected through hyperedge HE-4 (induced by source paper "qr2 a third party query reranking service over web databases"):
  with members:
    - "discovering the skyline of web databases"
    - "optimal algorithms for crawling a hidden database in the web"
    - "optimal aggregation algorithms for middleware"

Connected through hyperedge HE-5 (induced by source paper "designing fair ranking schemes"):
  with members:
    - "ranking with fairness constraints"
    - "runaway feedback loops in predictive policing"
    - "measuring fairness in ranked outputs"
    - "on the im possibility of fairness"
    - "discovering the skyline of web databases"
    - "fairness through awareness"

Connected through hyperedge HE-6 (induced by source paper "assisting service providers in peer to peer marketplaces maximizing gain over flexible attributes"):
  with members:
    - "constrained monotone function maximization and the supermodular degree"

Question: Please tell me which class the center node 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.DB(Databases)