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 for automatic ranking of participants and tasks in an anonymized contest"):
  Abstract: We introduce a new set of problems based on the Chain Editing problem. In our version of Chain Editing, we are given a set of anonymous participants and a set of undisclosed tasks that every participant attempts. For each participant-task pair, we know whether the participant has succeeded at the task or not. We assume that participants vary in their ability to solve tasks, and that tasks vary in their difficulty to be solved. In an ideal world, stronger participants should succeed at a superset of tasks that weaker participants succeed at. Similarly, easier tasks should be completed successfully by a superset of participants who succeed at harder tasks. In reality, it can happen that a stronger participant fails at a task that a weaker participants succeeds at. Our goal is to find a perfect nesting of the participant-task relations by flipping a minimum number of participant-task relations, implying such a "nearest perfect ordering" to be the one that is closest to the truth of participant strengths and task difficulties. Many variants of the problem are known to be NP-hard. #R##N#We propose six natural $k$-near versions of the Chain Editing problem and classify their complexity. The input to a $k$-near Chain Editing problem includes an initial ordering of the participants (or tasks) that we are required to respect by moving each participant (or task) at most $k$ positions from the initial ordering. We obtain surprising results on the complexity of the six $k$-near problems: Five of the problems are polynomial-time solvable using dynamic programming, but one of them is NP-hard.

Includes members:
  Member "minimum fill in inapproximability and almost tight lower bounds":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a fast minimum degree algorithm and matching lower bound")
  Member "lower bounds for the parameterized complexity of minimum fill in and other completion problems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a fast minimum degree algorithm and matching lower bound")
  Member "on the threshold of intractability":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "faster and enhanced inclusion minimal cograph completion")
  Member "a survey on truth discovery":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint inference on truth rumor and their sources in social networks")
  Member "chordal editing is fixed parameter tractable":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a polynomial kernel for 3 leaf power deletion")
  Member "subexponential parameterized algorithm for minimum fill in":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs")
  Member "data conflict resolution using trust mappings":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "linearized and single pass belief propagation")

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)