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: "range predecessor and lempel ziv parsing"
  Abstract: The Lempel-Ziv parsing of a string (LZ77 for short) is one of the most important and widely-used algorithmic tools in data compression and string processing. We show that the Lempel-Ziv parsing of a string of length $n$ on an alphabet of size $\sigma$ can be computed in $O(n\log\log\sigma)$ time ($O(n)$ time if we allow randomization) using $O(n\log\sigma)$ bits of working space; that is, using space proportional to that of the input string in bits. The previous fastest algorithm using $O(n\log\sigma)$ space takes $O(n(\log\sigma+\log\log n))$ time. We also consider the important rightmost variant of the problem, where the goal is to associate with each phrase of the parsing its most recent occurrence in the input string. We solve this problem in $O(n(1 + (\log\sigma/\sqrt{\log n}))$ time, using the same working space as above. The previous best solution for rightmost parsing uses $O(n(1+\log\sigma/\log\log n))$ time and $O(n\log n)$ space. As a bonus, in our solution for rightmost parsing we provide a faster construction method for efficient 2D orthogonal range reporting, which is of independent interest.

Connected through hyperedge HE-1 (induced by source paper "computing runs on a trie"):
  with members:
    - "near optimal computation of runs over general alphabet via non crossing lce queries"

Connected through hyperedge HE-2 (induced by source paper "universal compressed text indexing"):
  with members:
    - "fast prefix search in little space with applications"
    - "time space trade offs for lempel ziv compressed indexing"
    - "at the roots of dictionary compression string attractors"
    - "compressed indexing with signature grammars"
    - "fast label extraction in the cdawg"
    - "optimal time text indexing in bwt runs bounded space"
    - "sparse suffix tree construction in optimal time and space"
    - "a self index on block trees"

Connected through hyperedge HE-3 (induced by source paper "refining the r index"):
  with members:
    - "conversion from rlbwt to lz77"
    - "fully functional suffix trees and optimal text searching in bwt runs bounded space"
    - "lower bounds for text indexing with mismatches and differences"
    - "efficient construction of a complete index for pan genomics read alignment"
    - "prefix free parsing for building big bwts"
    - "from lz77 to the run length encoded burrows wheeler transform and back"
    - "a framework of dynamic data structures for string processing"
    - "optimal construction of compressed indexes for highly repetitive texts"

Connected through hyperedge HE-4 (induced by source paper "optimal time dictionary compressed indexes"):
  with members:
    - "optimal rank and select queries on dictionary compressed text"
    - "fast prefix search in little space with applications"
    - "universal compressed text indexing"
    - "representing the suffix tree with the cdawg"
    - "time space trade offs for lempel ziv compressed indexing"
    - "at the roots of dictionary compression string attractors"
    - "compressed indexing with signature grammars"
    - "document listing on repetitive collections with guaranteed performance"

Connected through hyperedge HE-5 (induced by source paper "text indexing and searching in sublinear time"):
  with members:
    - "orthogonal point location and rectangle stabbing queries in 3 d"
    - "fast compressed self indexes with deterministic linear time construction"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "sparse suffix tree construction in optimal time and space"
    - "deterministic indexing for packed strings"
    - "wavelet trees meet suffix trees"
    - "suffix trays and suffix trists structures for faster text indexing"
    - "alphabet dependent string searching with wexponential search trees"

Connected through hyperedge HE-6 (induced by source paper "practical evaluation of lempel ziv 78 and lempel ziv welch tries"):
  with members:
    - "dynamic space efficient hashing"
    - "compression with the tudocomp framework"
    - "faster 64 bit universal hashing using carry less multiplications"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "lempel ziv computation in compressed space lz cics"
    - "alphabet dependent string searching with wexponential search trees"
    - "lightweight lempel ziv parsing"
    - "lz compressed string dictionaries"

Connected through hyperedge HE-7 (induced by source paper "relations between greedy and bit optimal lz77 encodings"):
  with members:
    - "note on the greedy parsing optimality for dictionary based text compression"
    - "the rightmost equal cost position problem"

Connected through hyperedge HE-8 (induced by source paper "space efficient construction of compressed indexes in deterministic linear time"):
  with members:
    - "linear time string indexing and analysis in small space"
    - "dynamic data structures for document collections and graphs"
    - "linear time construction of compressed text indices in compact space"
    - "optimal dynamic sequence representations"
    - "efficient fully compressed sequence representations"
    - "more haste less waste lowering the redundancy in fully indexable dictionaries"
    - "fully functional static and dynamic succinct trees"

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)