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: "detecting 2 joins faster"
  Abstract: 2-Joins are edge cutsets that naturally appear in the decomposition of several classes of graphs closed under taking induced subgraphs, such as balanced bipartite graphs, even-hole-free graphs, perfect graphs and claw-free graphs. Their detection is needed in several algorithms, and is the slowest step for some of them. The classical method to detect a 2-join takes O(n^3m) time where n is the number of vertices of the input graph and m is the number of its edges. To detect non-path 2-joins (special kinds of 2-joins that are needed in all of the known algorithms that use 2-joins), the fastest known method takes time O(n^4m). Here, we give an O(n^2m)-time algorithm for both of these problems. A consequence is a speed-up of several known algorithms.

Connected through hyperedge HE-1 (induced by source paper "three in a tree in near linear time"):
  with members:
    - "graph pattern detection hardness for all induced patterns and faster non induced cycles"
    - "a faster algorithm to recognize even hole free graphs"
    - "on the structure of pan even hole free graphs"
    - "powers of tensors and fast matrix multiplication"
    - "detecting an induced net subdivision"
    - "large induced subgraphs via triangulations and cmso"
    - "induced disjoint paths in claw free graphs"
    - "the k in a path problem for claw free graphs"

Connected through hyperedge HE-2 (induced by source paper "a faster algorithm to recognize even hole free graphs"):
  with members:
    - "combinatorial optimization with 2 joins"
    - "algorithms for perfectly contractile graphs"

Connected through hyperedge HE-3 (induced by source paper "coloring perfect graphs with no balanced skew partitions"):
  with members:
    - "combinatorial optimization with 2 joins"

Connected through hyperedge HE-4 (induced by source paper "domination when the stars are out"):
  with members:
    - "normal helly circular arc graphs and its subclasses"
    - "deterministic parameterized connected vertex cover"
    - "parameterized complexity of induced graph matching on claw free graphs"
    - "optimal antithickenings of claw free trigraphs"
    - "dominating set is fixed parameter tractable in claw free graphs"
    - "linear time split decomposition revisited"
    - "solving dominating set in larger classes of graphs fpt algorithms and polynomial kernels"

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.DS(Data Structures and Algorithms)