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: "semantic optimization of preference queries"
  Abstract: The notion of preference is becoming more and more ubiquitous in present-day information systems. Preferences are primarily used to filter and personalize the information reaching the users of such systems. In database systems, preferences are usually captured as preference relations that are used to build preference queries. In our approach, preference queries are relational algebra or SQL queries that contain occurrences of the winnow operator ("find the most preferred tuples in a given relation"). #R##N#We present here a number of semantic optimization techniques applicable to preference queries. The techniques make use of integrity constraints, and make it possible to remove redundant occurrences of the winnow operator and to apply a more efficient algorithm for the computation of winnow. We also study the propagation of integrity constraints in the result of the winnow. We have identified necessary and sufficient conditions for the applicability of our techniques, and formulated those conditions as constraint satisfiability problems.

Connected through hyperedge HE-1 (induced by source paper "database querying under changing preferences"):
  with members:
    - "semantic optimization techniques for preference queries"
    - "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements"

Connected through hyperedge HE-2 (induced by source paper "monotonic and nonmonotonic preference revision"):
  with members:
    - "cp nets a tool for representing and reasoning with conditional ceteris paribus preference statements"

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)