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: "the complexity of approximately counting tree homomorphisms"
  Abstract: We study two computational problems, parameterised by a fixed tree H. #HOMSTO(H) is the problem of counting homomorphisms from an input graph G to H. #WHOMSTO(H) is the problem of counting weighted homomorphisms to H, given an input graph G and a weight function for each vertex v of G. Even though H is a tree, these problems turn out to be sufficiently rich to capture all of the known approximation behaviour in #P. We give a complete trichotomy for #WHOMSTO(H). If H is a star, then #WHOMSTO(H) is in FP. If H is not a star but it does not contain a certain induced subgraph J3, then #WHOMSTO(H) is equivalent under approximation-preserving (AP) reductions to #BIS, the problem of counting independent sets in a bipartite graph. This problem is complete for the class #RHΠ1 under AP-reductions. Finally, if H contains an induced J3, then #WHOMSTO(H) is equivalent under AP-reductions to #SAT, the problem of counting satisfying assignments to a CNF Boolean formula. Thus, #WHOMSTO(H) is complete for #P under AP-reductions. The results are similar for #HOMSTO(H) except that a rich structure emerges if H contains an induced J3. We show that there are trees H for which #HOMSTO(H) is #SAT-equivalent (disproving a plausible conjecture of Kelk). However, it is still not known whether #HOMSTO(H) is #SAT-hard for every tree H which contains an induced J3. It turns out that there is an interesting connection between these homomorphism-counting problems and the problem of approximating the partition function of the ferromagnetic Potts model. In particular, we show that for a family of graphs Jq, parameterised by a positive integer q, the problem #HOMSTO(Jq) is AP-interreducible with the problem of approximating the partition function of the q-state Potts model. It was not previously known that the Potts model had a homomorphism-counting interpretation. We use this connection to obtain some additional upper bounds for the approximation complexity of #HOMSTO(Jq).

Connected through hyperedge HE-1 (induced by source paper "the complexity of approximately counting retractions to square free graphs"):
  with members:
    - "counting homomorphisms modulo a prime number"
    - "a dichotomy theorem for nonuniform csps"
    - "counting homomorphisms to square free graphs modulo 2"
    - "the complexity of surjective homomorphism problems a survey"

Connected through hyperedge HE-2 (induced by source paper "the complexity of approximately counting retractions"):
  with members:
    - "surjective h colouring new hardness results"
    - "a dichotomy theorem for nonuniform csps"
    - "approximately counting h colourings is bis hard"
    - "ferromagnetic potts model refined bis hardness and related results"
    - "the complexity of surjective homomorphism problems a survey"
    - "an approximation trichotomy for boolean csp"

Connected through hyperedge HE-3 (induced by source paper "approximately counting locally optimal structures"):
  with members:
    - "unique perfect phylogeny characterizations via uniquely representable chordal graphs"
    - "approximating the partition function of the ferromagnetic potts model"
    - "finding induced subgraphs via minimal triangulations"
    - "treewidth computation and extremal combinatorics"

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.CC(Computational Complexity)