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: "on the complexity of mining itemsets from the crowd using taxonomies"
  Abstract: We study the problem of frequent itemset mining in domains where data is not recorded in a conventional database but only exists in human knowledge. We provide examples of such scenarios, and present a crowdsourcing model for them. The model uses the crowd as an oracle to find out whether an itemset is frequent or not, and relies on a known taxonomy of the item domain to guide the search for frequent itemsets. In the spirit of data mining with oracles, we analyze the complexity of this problem in terms of (i) crowd complexity, that measures the number of crowd questions required to identify the frequent itemsets; and (ii) computational complexity, that measures the computational effort required to choose the questions. We provide lower and upper complexity bounds in terms of the size and structure of the input taxonomy, as well as the size of a concise description of the output itemsets. We also provide constructive algorithms that achieve the upper bounds, and consider more efficient variants for practical situations.

Connected through hyperedge HE-1 (induced by source paper "select your questions wisely for entity resolution with crowd errors"):
  with members:
    - "leveraging transitive relations for crowdsourced joins"
    - "evaluating the crowd with confidence"
    - "cdas a crowdsourcing data analytics system"
    - "crowder crowdsourcing entity resolution"
    - "whom to ask jury selection for decision making tasks on micro blog services"
    - "human assisted graph search it s okay to ask questions"
    - "human powered sorts and joins"

Connected through hyperedge HE-2 (induced by source paper "top k querying of unknown values under order constraints"):
  with members:
    - "possible and certain answers for queries over order incomplete data"
    - "uncertainty in crowd data sourcing under structural constraints"
    - "a fast and practical method to estimate volumes of convex polytopes"
    - "human assisted graph search it s okay to ask questions"
    - "a unified approach to ranking in probabilistic databases"
    - "semantics and evaluation of top k queries in probabilistic databases"

Connected through hyperedge HE-3 (induced by source paper "structurally tractable uncertain data"):
  with members:
    - "declarative statistical modeling with datalog"
    - "uncertainty in crowd data sourcing under structural constraints"
    - "probabilistic databases with markoviews"

Connected through hyperedge HE-4 (induced by source paper "uncertainty in crowd data sourcing under structural constraints"):
  with members:
    - "human assisted graph search it s okay to ask questions"

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)