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: "the k mismatch problem revisited"
  Abstract: We revisit the complexity of one of the most basic problems in pattern matching. In the k-mismatch problem we must compute the Hamming distance between a pattern of length m and every m-length substring of a text of length n, as long as that Hamming distance is at most k. Where the Hamming distance is greater than k at some alignment of the pattern and text, we simply output "No". #R##N#We study this problem in both the standard offline setting and also as a streaming problem. In the streaming k-mismatch problem the text arrives one symbol at a time and we must give an output before processing any future symbols. Our main results are as follows: #R##N#1) Our first result is a deterministic $O(n k^2\log{k} / m+n \text{polylog} m)$ time offline algorithm for k-mismatch on a text of length n. This is a factor of k improvement over the fastest previous result of this form from SODA 2000 by Amihood Amir et al. #R##N#2) We then give a randomised and online algorithm which runs in the same time complexity but requires only $O(k^2\text{polylog} {m})$ space in total. #R##N#3) Next we give a randomised $(1+\epsilon)$-approximation algorithm for the streaming k-mismatch problem which uses $O(k^2\text{polylog} m / \epsilon^2)$ space and runs in $O(\text{polylog} m / \epsilon^2)$ worst-case time per arriving symbol. #R##N#4) Finally we combine our new results to derive a randomised $O(k^2\text{polylog} {m})$ space algorithm for the streaming k-mismatch problem which runs in $O(\sqrt{k}\log{k} + \text{polylog} {m})$ worst-case time per arriving symbol. This improves the best previous space complexity for streaming k-mismatch from FOCS 2009 by Benny Porat and Ely Porat by a factor of k. We also improve the time complexity of this previous result by an even greater factor to match the fastest known offline algorithm (up to logarithmic factors).

Connected through hyperedge HE-1 (induced by source paper "approximating text to pattern hamming distances"):
  with members:
    - "l p pattern matching in a stream"
    - "string synchronizing sets sublinear time bwt construction and optimal lce data structure"
    - "the streaming k mismatch problem"
    - "improved rectangular matrix multiplication using powers of the coppersmith winograd tensor"
    - "parameter free locality sensitive hashing for spherical range reporting"
    - "optimal hashing based time space trade offs for approximate near neighbors"
    - "polynomial representations of threshold functions and algorithmic applications"
    - "approximate hamming distance in a stream"

Connected through hyperedge HE-2 (induced by source paper "sliding window property testing for regular languages"):
  with members:
    - "visibly pushdown languages over sliding windows"
    - "randomized sliding window algorithms for regular languages"
    - "automata theory on sliding windows"
    - "streaming pattern matching with d wildcards"
    - "approximate hamming distance in a stream"
    - "dictionary matching in a stream"
    - "streaming property testing of visibly pushdown languages"
    - "streaming algorithms for recognizing nearly well parenthesized expressions"

Connected through hyperedge HE-3 (induced by source paper "l p pattern matching in a stream"):
  with members:
    - "approximating approximate pattern matching"
    - "the streaming k mismatch problem"
    - "approximate hamming distance in a stream"
    - "how to catch l 2 heavy hitters on sliding windows"
    - "an optimal lower bound on the communication complexity of gap hamming distance"

Connected through hyperedge HE-4 (induced by source paper "circular pattern matching with k mismatches"):
  with members:
    - "efficient representation and counting of antipower factors in words"
    - "the streaming k mismatch problem"
    - "average case optimal approximate circular string matching"
    - "internal pattern matching queries in a text and applications"
    - "beating o nm in approximate lzw compressed pattern matching"

Connected through hyperedge HE-5 (induced by source paper "periodicity in data streams with wildcards"):
  with members:
    - "the streaming k mismatch problem"
    - "streaming periodicity with mismatches"
    - "streaming pattern matching with d wildcards"
    - "tight tradeoffs for real time approximation of longest palindromes in streams"
    - "streaming k mismatch with error correcting and applications"
    - "dictionary matching in a stream"
    - "space efficient string indexing for wildcard pattern matching"
    - "space lower bounds for online pattern matching"

Connected through hyperedge HE-6 (induced by source paper "visibly pushdown languages over sliding windows"):
  with members:
    - "automata theory on sliding windows"
    - "dictionary matching in a stream"
    - "streaming property testing of visibly pushdown languages"
    - "streaming algorithms for language recognition problems"
    - "recognizing well parenthesized expressions in the streaming model"

Connected through hyperedge HE-7 (induced by source paper "approximating approximate pattern matching"):
  with members:
    - "taylor polynomial estimator for estimating frequency moments"
    - "an optimal lower bound on the communication complexity of gap hamming distance"

Connected through hyperedge HE-8 (induced by source paper "fine grained complexity of analyzing compressed data quantifying improvements over decompress and solve"):
  with members:
    - "truly sub cubic algorithms for language edit distance and rna folding via fast bounded difference min plus product"
    - "why is it hard to beat o n 2 for longest common weakly increasing subsequence"
    - "a dichotomy for regular expression membership testing"
    - "conditional lower bound for rna folding problem"
    - "clustered integer 3sum via additive combinatorics"
    - "which regular expression patterns are hard to match"
    - "simulating branching programs with edit distance and friends or a polylog shaved is a lower bound made"
    - "if the current clique algorithms are optimal so is valiant s parser"

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)