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 "general and fractional hypertree decompositions hard and easy cases"):
  Abstract: Hypertree decompositions, as well as the more powerful generalized hypertree decompositions (GHDs), and the yet more general fractional hypertree decompositions (FHD) are hypergraph decomposition methods successfully used for answering conjunctive queries and for the solution of constraint satisfaction problems. Every hypergraph H has a width relative to each of these decomposition methods: its hypertree width hw(H), its generalized hypertree width ghw(H), and its fractional hypertree width fhw(H), respectively. #R##N#It is known that hw(H) <= k can be checked in polynomial time for fixed k, while checking ghw(H) <= k is NP-complete for any k greater than or equal to 3. The complexity of checking fhw(H) <= k for a fixed k has been open for more than a decade. #R##N#We settle this open problem by showing that checking fhw(H) <= k is NP-complete, even for k=2. The same construction allows us to prove also the NP-completeness of checking ghw(H) <= k for k=2. After proving these hardness results, we identify meaningful restrictions, for which checking for bounded ghw or fhw becomes tractable.

Includes members:
  Member "size bounds and query plans for relational joins":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "complexity analysis of general and fractional hypertree decompositions")
  Member "constraint solving via fractional edge covers":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "complexity analysis of general and fractional hypertree decompositions")
  Member "an analytical study of large sparql query logs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "knowledge graphs")
  Member "old techniques for new join algorithms a case study in rdf processing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "complexity analysis of general and fractional hypertree decompositions")
  Member "myhill nerode methods for hypergraphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "complexity analysis of general and fractional hypertree decompositions")
  Member "faq questions asked frequently":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "complexity analysis of general and fractional hypertree decompositions")
  Member "joins via geometric resolutions worst case and beyond":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "complexity analysis of general and fractional hypertree decompositions")
  Member "gym a multiround join algorithm in mapreduce":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "complexity analysis of general and fractional hypertree decompositions")

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.DB(Databases)