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: "fully online grammar compression in constant space"
  Abstract: We present novel variants of fully online LCA (FOLCA), a fully online grammar compression that builds a straight line program (SLP) and directly encodes it into a succinct representation in an online manner. FOLCA enables a direct encoding of an SLP into a succinct representation that is asymptotically equivalent to an information theoretic lower bound for representing an SLP (Maruyama et al., SPIRE'13). The compression of FOLCA takes linear time proportional to the length of an input text and its working space depends only on the size of the SLP, which enables us to apply FOLCA to large-scale repetitive texts. Recent repetitive texts, however, include some noise. For example, current sequencing technology has significant error rates, which embeds noise into genome sequences. For such noisy repetitive texts, FOLCA working in the SLP size consumes a large amount of memory. We present two variants of FOLCA working in constant space by leveraging the idea behind stream mining techniques. Experiments using 100 human genomes corresponding to about 300GB from the 1000 human genomes project revealed the applicability of our method to large-scale, noisy repetitive texts.

Connected through hyperedge HE-1 (induced by source paper "grammar compression with probabilistic context free grammar"):
  with members:
    - "mr repair grammar compression based on maximal repeats"
    - "a grammar compression algorithm based on induced suffix sorting"
    - "space efficient re pair compression"
    - "faster fully compressed pattern matching by recompression"
    - "tree structure compression with repair"

Connected through hyperedge HE-2 (induced by source paper "siedm an efficient string index and search algorithm for edit distance with moves"):
  with members:
    - "online self indexed grammar compression"
    - "online pattern matching for string edit distance with moves"
    - "searching and indexing genomic databases via kernelization"
    - "improved esp index a practical self index for highly repetitive texts"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"

Connected through hyperedge HE-3 (induced by source paper "online self indexed grammar compression"):
  with members:
    - "improved esp index a practical self index for highly repetitive texts"
    - "improved grammar based compressed indexes"
    - "a faster grammar based self index"
    - "fully functional static and dynamic succinct trees"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"

Connected through hyperedge HE-4 (induced by source paper "approximating lz77 in small space"):
  with members:
    - "searching and indexing genomic databases via kernelization"
    - "lempel ziv parsing in external memory"

Connected through hyperedge HE-5 (induced by source paper "searching and indexing genomic databases via kernelization"):
  with members:
    - "hybrid indexes for repetitive datasets"
    - "improved esp index a practical self index for highly repetitive texts"
    - "indexes of large genome collections on a pc"
    - "data structure lower bounds on random access to grammar compressed strings"
    - "faster approximate pattern matching in compressed repetitive texts"
    - "improved grammar based compressed indexes"
    - "random access to grammar compressed strings"

Connected through hyperedge HE-6 (induced by source paper "online pattern matching for string edit distance with moves"):
  with members:
    - "pattern matching in multiple streams"
    - "space lower bounds for online pattern matching"
    - "parameterized matching in the streaming model"
    - "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)