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: "large alphabets and incompressibility"
  Abstract: We briefly survey some concepts related to empirical entropy--normal numbers, de Bruijn sequences and Markov processes-- and investigate how well it approximates Kolmogorov complexity. Our results suggest lth-order empirical entropy stops being a reasonable complexity metric for almost all strings of length m over alphabets of size n about when nl surpasses m.

Connected through hyperedge HE-1 (induced by source paper "lempel ziv like parsing in small space"):
  with members:
    - "at the roots of dictionary compression string attractors"
    - "relations between greedy and bit optimal lz77 encodings"
    - "lz end parsing in compressed space"
    - "approximating lz77 via small space multiple pattern matching"
    - "from theory to practice plug and play with succinct data structures"
    - "lempel ziv parsing in external memory"
    - "linear time lempel ziv factorization simple fast small"
    - "relative lempel ziv factorization for efficient storage and retrieval of web collections"

Connected through hyperedge HE-2 (induced by source paper "entropy bounds for grammar based tree compressors"):
  with members:
    - "grammar based compression of unranked trees"
    - "using statistical encoding to achieve tree succinctness never seen before"
    - "entropy bounds for grammar compression"
    - "a universal tree balancing theorem"
    - "universal tree source coding using grammar based compression"
    - "a universal grammar based code for lossless compression of binary trees"
    - "identifying hierarchical structure in sequences a linear time algorithm"

Connected through hyperedge HE-3 (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-4 (induced by source paper "on the approximation ratio of greedy parsings"):
  with members:
    - "optimal time dictionary compressed indexes"
    - "at the roots of dictionary compression string attractors"
    - "compression with the tudocomp framework"
    - "optimal time text indexing in bwt runs bounded space"
    - "a separation between run length slps and lz77"
    - "fully dynamic data structure for lce queries in compressed space"
    - "composite repetition aware data structures"
    - "factorizations of the fibonacci infinite word"

Connected through hyperedge HE-5 (induced by source paper "compressed multiple pattern matching"):
  with members:
    - "greedy shortest common superstring approximation in compact space"
    - "dictionary matching in a stream"
    - "engineering small space dictionary matching"
    - "fixed block compression boosting in fm indexes"
    - "succinct dictionary matching with no slowdown"

Connected through hyperedge HE-6 (induced by source paper "fast compressed self indexes with deterministic linear time construction"):
  with members:
    - "fast prefix search in little space with applications"
    - "linear time string indexing and analysis in small space"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "deterministic indexing for packed strings"
    - "linear time construction of compressed text indices in compact space"
    - "suffix trays and suffix trists structures for faster text indexing"
    - "alphabet dependent string searching with wexponential search trees"
    - "optimal lower and upper bounds for representing sequences"

Connected through hyperedge HE-7 (induced by source paper "at the roots of dictionary compression string attractors"):
  with members:
    - "representing the suffix tree with the cdawg"
    - "time space trade offs for lempel ziv compressed indexing"
    - "fast label extraction in the cdawg"
    - "optimal time text indexing in bwt runs bounded space"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "fully dynamic data structure for lce queries in compressed space"
    - "composite repetition aware data structures"
    - "linear time construction of compressed text indices in compact space"

Connected through hyperedge HE-8 (induced by source paper "fast label extraction in the cdawg"):
  with members:
    - "representing the suffix tree with the cdawg"
    - "linear size cdawg new repetition aware indexing and grammar compression"
    - "traversing grammar compressed trees with constant delay"
    - "composite repetition aware data structures"

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.IT(Information Theory)