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: "world set decompositions expressiveness and efficient algorithms"
  Abstract: Uncertain information is commonplace in real-world data management scenarios. The ability to represent large sets of possible instances (worlds) while supporting efficient storage and processing is an important challenge in this context. The recent formalism of world-set decompositions (WSDs) provides a space-efficient representation for uncertain data that also supports scalable processing. WSDs are complete for finite world-sets in that they can represent any finite set of possible worlds. For possibly infinite world-sets, we show that a natural generalization of WSDs precisely captures the expressive power of c-tables. We then show that several important decision problems are efficiently solvable on WSDs while they are NP-hard on c-tables. Finally, we give a polynomial-time algorithm for factorizing WSDs, i.e. an efficient algorithm for minimizing such representations.

Connected through hyperedge HE-1 (induced by source paper "computing possible and certain answers over order incomplete data"):
  with members:
    - "computational social choice meets databases"
    - "topological sorting under regular constraints"
    - "possible and certain answers for queries over order incomplete data"
    - "determining possible and necessary winners under common voting rules given partial orders"
    - "taking the final step to a full dichotomy of the possible winner problem in pure scoring rules"
    - "towards a dichotomy for the possible winner problem in elections based on scoring rules"
    - "optimal aggregation algorithms for middleware"

Connected through hyperedge HE-2 (induced by source paper "incremental view maintenance with triple lock factorization benefits"):
  with members:
    - "answering conjunctive queries under updates"
    - "in database learning with sparse tensors"
    - "towards linear algebra over normalized data"
    - "mllib machine learning in apache spark"
    - "faq questions asked frequently"
    - "linview incremental view maintenance for complex analytical queries"
    - "aggregation and ordering in factorised databases"
    - "skew strikes back new developments in the theory of join algorithms"

Connected through hyperedge HE-3 (induced by source paper "self correlation and maximum independence in finite relations"):
  with members:
    - "dependence and independence"
    - "10 10 6 worlds and beyond efficient representation and processing of incomplete information"

Connected through hyperedge HE-4 (induced by source paper "aggregation and ordering in factorised databases"):
  with members:
    - "constraint solving via fractional edge covers"
    - "fdb a query engine for factorised relational databases"
    - "on minimal constraint networks"
    - "the case for rodentstore an adaptive declarative storage system"

Connected through hyperedge HE-5 (induced by source paper "fdb a query engine for factorised relational databases"):
  with members:
    - "constraint solving via fractional edge covers"
    - "on minimal constraint networks"

Connected through hyperedge HE-6 (induced by source paper "on minimal constraint networks"):
  with members:
    - "hypertree decompositions and tractable queries"

Connected through hyperedge HE-7 (induced by source paper "semantics and evaluation of top k queries in probabilistic databases"):
  with members:
    - "optimal aggregation algorithms for middleware"

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)