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: "which regular expression patterns are hard to match"
  Abstract: Regular expressions constitute a fundamental notion in formal language theory and are frequently used in computer science to define search patterns. A classic algorithm for these problems constructs and simulates a non-deterministic finite automaton corresponding to the expression, resulting in an $O(mn)$ running time (where $m$ is the length of the pattern and $n$ is the length of the text). This running time can be improved slightly (by a polylogarithmic factor), but no significantly faster solutions are known. At the same time, much faster algorithms exist for various special cases of regular expressions, including dictionary matching, wildcard matching, subset matching, word break problem etc. #R##N#In this paper, we show that the complexity of regular expression matching can be characterized based on its {\em depth} (when interpreted as a formula). Our results hold for expressions involving concatenation, OR, Kleene star and Kleene plus. For regular expressions of depth two (involving any combination of the above operators), we show the following dichotomy: matching and membership testing can be solved in near-linear time, except for "concatenations of stars", which cannot be solved in strongly sub-quadratic time assuming the Strong Exponential Time Hypothesis (SETH). For regular expressions of depth three the picture is more complex. Nevertheless, we show that all problems can either be solved in strongly sub-quadratic time, or cannot be solved in strongly sub-quadratic time assuming SETH. #R##N#An intriguing special case of membership testing involves regular expressions of the form "a star of an OR of concatenations", e.g., $[a|ab|bc]^*$. This corresponds to the so-called {\em word break} problem, for which a dynamic programming algorithm with a runtime of (roughly) $O(n\sqrt{m})$ is known. We show that the latter bound is not tight and improve the runtime to $O(nm^{0.44\ldots})$.

Connected through hyperedge HE-1 (induced by source paper "graphs cannot be indexed in polynomial time for sub quadratic time string matching unless seth fails"):
  with members:
    - "regular languages meet prefix sorting"
    - "on prefix sorting finite automata"
    - "on the hardness and inapproximability of recognizing wheeler graphs"
    - "on the hardness of set disjointness and set intersection with bounded universe"
    - "lower bounds for text indexing with mismatches and differences"
    - "indexing variation graphs"
    - "distributed pcp theorems for hardness of approximation in p"
    - "improving viterbi is hard better runtimes imply faster clique algorithms"

Connected through hyperedge HE-2 (induced by source paper "on the complexity of exact pattern matching in graphs binary strings and bounded degree"):
  with members:
    - "on the complexity of exact pattern matching in graphs determinism and zig zag matching"
    - "the gremlin graph traversal machine and language invited talk"
    - "a survey of heterogeneous information network analysis"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"
    - "defining and evaluating network communities based on ground truth"

Connected through hyperedge HE-3 (induced by source paper "regular languages meet prefix sorting"):
  with members:
    - "on the hardness and inapproximability of recognizing wheeler graphs"
    - "optimal time text indexing in bwt runs bounded space"
    - "optimal dynamic sequence representations"
    - "improved grammar based compressed indexes"

Connected through hyperedge HE-4 (induced by source paper "sparse regular expression matching"):
  with members:
    - "new algorithms for regular expression matching"
    - "fast and compact regular expression matching"

Connected through hyperedge HE-5 (induced by source paper "more consequences of falsifying seth and the orthogonal vectors conjecture"):
  with members:
    - "on the fine grained complexity of empirical risk minimization kernel methods and neural networks"
    - "conditional lower bounds for all pairs max flow"
    - "on the fine grained complexity of one dimensional dynamic programming"
    - "distributed pcp theorems for hardness of approximation in p"
    - "tree edit distance cannot be computed in strongly subcubic time unless apsp can"
    - "fine grained complexity of analyzing compressed data quantifying improvements over decompress and solve"
    - "improving viterbi is hard better runtimes imply faster clique algorithms"
    - "on the hardness of partially dynamic graph problems and connections to diameter"

Connected through hyperedge HE-6 (induced by source paper "on the hardness of approximate and exact bichromatic maximum inner product"):
  with members:
    - "hardness of approximate nearest neighbor search"
    - "conditional lower bounds for all pairs max flow"
    - "conditional lower bounds for space time tradeoffs"
    - "distributed pcp theorems for hardness of approximation in p"
    - "on the parameterized complexity of approximating dominating set"
    - "improved rectangular matrix multiplication using powers of the coppersmith winograd tensor"
    - "on the complexity of closest pair via polar pair of point sets"
    - "a framework for similarity search with space time tradeoffs using locality sensitive filtering"

Connected through hyperedge HE-7 (induced by source paper "fine grained complexity meets ip pspace"):
  with members:
    - "on problems equivalent to min convolution"
    - "hardness of approximate nearest neighbor search"
    - "on the hardness of approximate and exact bichromatic maximum inner product"
    - "tighter connections between formula sat and shaving logs"
    - "conditional lower bounds for all pairs max flow"
    - "conditional lower bounds for space time tradeoffs"
    - "conditional hardness for sensitivity problems"
    - "on the parameterized complexity of approximating dominating set"

Connected through hyperedge HE-8 (induced by source paper "tighter connections between formula sat and shaving logs"):
  with members:
    - "subquadratic algorithms for succinct stable matching"
    - "a dichotomy for regular expression membership testing"
    - "an improved combinatorial algorithm for boolean matrix multiplication"
    - "improved bounds for 3sum k sum and linear degeneracy"
    - "fr echet distance for curves revisited"
    - "subtree isomorphism revisited"
    - "simulating branching programs with edit distance and friends or a polylog shaved is a lower bound made"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"

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)