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: "longest common subsequence on weighted sequences"
  Abstract: We consider the general problem of the Longest Common Subsequence (LCS) on weighted sequences. Weighted sequences are an extension of classical strings, where in each position every letter of the alphabet may occur with some probability. In this paper we provide faster algorithms and prove a series of hardness results for more general variants of the problem. In particular, we provide an NP-Completeness result on the general variant of the problem instead of the log-probability version used in earlier papers, already for alphabets of size 2. Furthermore, we design an EPTAS for bounded alphabets, which is also an improved, compared to previous results, PTAS for unbounded alphabets. These are in a sense optimal, since it is known that there is no FPTAS for bounded alphabets, while we prove that there is no EPTAS for unbounded alphabets. Finally, we provide a matching conditional (under the Exponential Time Hypothesis) lower bound for any PTAS. As a side note, we prove that it is sufficient to work with only one threshold in the general variant of the problem.

Connected through hyperedge HE-1 (induced by source paper "weighted shortest common supersequence problem revisited"):
  with members:
    - "indexing weighted sequences neat and efficient"
    - "faster space efficient algorithms for subset sum k sum and related problems"
    - "pattern matching and consensus problems on weighted sequences and profiles"
    - "efficient index for weighted sequences"
    - "streaming k mismatch with error correcting and applications"

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)