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 "algorithms and hardness results for happy coloring problems"):
  Abstract: In a vertex-colored graph, an edge is happy if its endpoints have the same color. Similarly, a vertex is happy if all its incident edges are happy. Motivated by the computation of homophily in social networks, we consider the algorithmic aspects of the following Maximum Happy Edges (k-MHE) problem: given a partially k-colored graph G, find an extended full k-coloring of G maximizing the number of happy edges. When we want to maximize the number of happy vertices, the problem is known as Maximum Happy Vertices (k-MHV). We further study the complexity of the problems and their weighted variants. For instance, we prove that for every k >= 3, both problems are NP-complete for bipartite graphs and k-MHV remains hard for split graphs. In terms of exact algorithms, we show both problems can be solved in time O*(2^n), and give an even faster O*(1.89^n)-time algorithm when k = 3. From a parameterized perspective, we give a linear vertex kernel for Weighted k-MHE, where edges are weighted and the goal is to obtain happy edges of at least a specified total weight. Finally, we prove both problems are solvable in polynomial-time when the graph has bounded treewidth or bounded neighborhood diversity.

Includes members:
  Member "fixed parameter complexity of distance constrained labeling and uniform channel assignment problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "simplified algorithmic metatheorems beyond mso treewidth and neighborhood diversity")
  Member "using neighborhood diversity to solve hard problems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "iterated type partitions")

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.DS(Data Structures and Algorithms)