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 error correcting parser for context free grammars that takes less than cubic time"
  Abstract: The problem of parsing has been studied extensively for various formal grammars. Given an input string and a grammar, the parsing problem is to check if the input string belongs to the language generated by the grammar. A closely related problem of great importance is one where the input are a string ${\cal I}$ and a grammar $G$ and the task is to produce a string ${\cal I}'$ that belongs to the language generated by $G$ and the `distance' between ${\cal I}$ and ${\cal I}'$ is the smallest (from among all the strings in the language). Specifically, if ${\cal I}$ is in the language generated by $G$, then the output should be ${\cal I}$. Any parser that solves this version of the problem is called an {\em error correcting parser}. In 1972 Aho and Peterson presented a cubic time error correcting parser for context free grammars. Since then this asymptotic time bound has not been improved under the (standard) assumption that the grammar size is a constant. In this paper we present an error correcting parser for context free grammars that runs in $O(T(n))$ time, where $n$ is the length of the input string and $T(n)$ is the time needed to compute the tropical product of two $n\times n$ matrices. #R##N#In this paper we also present an $\frac{n}{M}$-approximation algorithm for the {\em language edit distance problem} that has a run time of $O(Mn^\omega)$, where $O(n^\omega)$ is the time taken to multiply two $n\times n$ matrices. To the best of our knowledge, no approximation algorithms have been proposed for error correcting parsing for general context free grammars.

Connected through hyperedge HE-1 (induced by source paper "reducing cascading parsing errors through fast error recovery"):
  with members:
    - "syntax error recovery in parsing expression grammars"

Connected through hyperedge HE-2 (induced by source paper "truly sub cubic algorithms for language edit distance and rna folding via fast bounded difference min plus product"):
  with members:
    - "clustered integer 3sum via additive combinatorics"
    - "hardness of rna folding problem with four symbols"
    - "if the current clique algorithms are optimal so is valiant s parser"
    - "powers of tensors and fast matrix multiplication"
    - "language edit distance maximum likelihood parsing of stochastic grammars faster algorithms connection to fundamental graph problems"
    - "faster all pairs shortest paths via circuit complexity"
    - "streaming algorithms for recognizing nearly well parenthesized expressions"
    - "faster algorithms for rectangular matrix multiplication"

Connected through hyperedge HE-3 (induced by source paper "if the current clique algorithms are optimal so is valiant s parser"):
  with members:
    - "an improved combinatorial algorithm for boolean matrix multiplication"
    - "clustered integer 3sum via additive combinatorics"
    - "time and space efficient algorithms for rna folding with the four russians technique"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"
    - "quadratic time hardness of lcs and other sequence similarity measures"
    - "powers of tensors and fast matrix multiplication"
    - "edit distance cannot be computed in strongly subquadratic time unless seth is false"
    - "language edit distance maximum likelihood parsing of stochastic grammars faster algorithms connection to fundamental graph problems"

Connected through hyperedge HE-4 (induced by source paper "language edit distance maximum likelihood parsing of stochastic grammars faster algorithms connection to fundamental graph problems"):
  with members:
    - "edit distance cannot be computed in strongly subquadratic time unless seth is false"
    - "faster all pairs shortest paths via circuit complexity"
    - "faster algorithms for rectangular matrix multiplication"
    - "fast context free grammar parsing requires fast boolean matrix multiplication"

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)