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: "exact algorithms for dominating induced matching based on graph partition"
  Abstract: A dominating induced matching, also called an efficient edge domination, of a graph $G=(V,E)$ with $n=|V|$ vertices and $m=|E|$ edges is a subset $F \subseteq E$ of edges in the graph such that no two edges in $F$ share a common endpoint and each edge in $E\setminus F$ is incident with exactly one edge in $F$. It is NP-hard to decide whether a graph admits a dominating induced matching or not. In this paper, we design a $1.1467^nn^{O(1)}$-time exact algorithm for this problem, improving all previous results. This problem can be redefined as a partition problem that is to partition the vertex set of a graph into two parts $I$ and $F$, where $I$ induces an independent set (a 0-regular graph) and $F$ induces a perfect matching (a 1-regular graph). After giving several structural properties of the problem, we show that the problem always contains some "good vertices", branching on which by including them to either $I$ or $F$ we can effectively reduce the graph. This leads to a fast exact algorithm to this problem.

Connected through hyperedge HE-1 (induced by source paper "perfect edge domination hard and solvable cases"):
  with members:
    - "efficient and perfect domination on circular arc graphs"
    - "dominating induced matchings in graphs containing no long claw"
    - "an o 1 1939 n time algorithm for minimum weighted dominating induced matching"
    - "exact algorithms for dominating induced matchings"
    - "efficient dominating and edge dominating sets for graphs and hypergraphs"

Connected through hyperedge HE-2 (induced by source paper "dominating induced matchings in graphs containing no long claw"):
  with members:
    - "an o 1 1939 n time algorithm for minimum weighted dominating induced matching"

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)