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: "an optimal decomposition algorithm for tree edit distance"
  Abstract: The edit distance between two ordered rooted trees with vertex labels is the minimum cost of transforming one tree into the other by a sequence of elementary operations consisting of deleting and relabeling existing nodes, as well as inserting new nodes. In this article, we present a worst-case O(n3)-time algorithm for the problem when the two trees have size n, improving the previous best O(n3 log n)-time algorithm. Our result requires a novel adaptive strategy for deciding how a dynamic program divides into subproblems, together with a deeper understanding of the previous algorithms for the problem. We prove the optimality of our algorithm among the family of decomposition strategy algorithms—which also includes the previous fastest algorithms—by tightening the known lower bound of Ω(n2 log2 n) to Ω(n3), matching our algorithm's running time. Furthermore, we obtain matching upper and lower bounds for decomposition strategy algorithms of Θ(nm2 (1 + log n/m)) when the two trees have sizes m and n and m

Connected through hyperedge HE-1 (induced by source paper "metric learning for ordered labeled trees with pq grams"):
  with members:
    - "tree edit distance learning via adaptive symbol embeddings"
    - "revisiting the tree edit distance and its backtracing a tutorial"
    - "adam a method for stochastic optimization"
    - "a survey on metric learning for feature vectors and structured data"
    - "a conditional random field for discriminatively trained finite state string edit distance"

Connected through hyperedge HE-2 (induced by source paper "the geometry of syntax and semantics for directed file transformations"):
  with members:
    - "dire a neural approach to decompiled identifier naming"
    - "synthesizing bijective lenses"
    - "tree edit distance cannot be computed in strongly subcubic time unless apsp can"
    - "a language theoretic view on network protocols"
    - "de bruijn entropy and string similarity"

Connected through hyperedge HE-3 (induced by source paper "new algorithms for unordered tree inclusion"):
  with members:
    - "when are tree structures necessary for deep learning of representations"

Connected through hyperedge HE-4 (induced by source paper "semantic document distance measures and unsupervised document revision detection"):
  with members:
    - "japanese english cross language information retrieval exploration of query translation and transliteration"

Connected through hyperedge HE-5 (induced by source paper "faster algorithms for the maximum common subtree isomorphism problem"):
  with members:
    - "on maximum common subgraph problems in series parallel graphs"
    - "subtree isomorphism revisited"
    - "an even faster and more unifying algorithm for comparing trees via unbalanced bipartite matchings"

Connected through hyperedge HE-6 (induced by source paper "a review on the tree edit distance problem and related path decomposition algorithms"):
  with members:
    - "rted a robust algorithm for the tree edit distance"

Connected through hyperedge HE-7 (induced by source paper "event driven agility of interoperability during the run time of collaborative processes"):
  with members:
    - "rted a robust algorithm for the tree edit distance"

Connected through hyperedge HE-8 (induced by source paper "adtool security analysis with attack defense trees extended version"):
  with members:
    - "quantitative questions on attack defense trees"
    - "rted a robust algorithm for the tree edit distance"

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)