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: "compressed text indexes from theory to practice"
  Abstract: A compressed full-text self-index represents a text in a compressed form and still answers queries efficiently. This technology represents a breakthrough over the text indexing techniques of the previous decade, whose indexes required several times the size of the text. Although it is relatively new, this technology has matured up to a point where theoretical research is giving way to practical developments. Nonetheless this requires significant programming skills, a deep engineering effort, and a strong algorithmic background to dig into the research results. To date only isolated implementations and focused comparisons of compressed indexes have been reported, and they missed a common API, which prevented their re-use or deployment within other applications. #R##N#The goal of this paper is to fill this gap. First, we present the existing implementations of compressed indexes from a practitioner's point of view. Second, we introduce the Pizza&Chili site, which offers tuned implementations and a standardized API for the most successful compressed full-text self-indexes, together with effective testbeds and scripts for their automatic validation and test. Third, we show the results of our extensive experiments on these codes with the aim of demonstrating the practical relevance of this novel and exciting technology.

Connected through hyperedge HE-1 (induced by source paper "a compact representation for trips over networks built on self indexes"):
  with members:
    - "cinct compression and retrieval for massive vehicular trajectories via relative movement labeling"
    - "compact trip representation over networks"
    - "efficient and compact representations of some non canonical prefix free codes"
    - "on compressing permutations and adaptive sorting"
    - "new algorithms on wavelet trees and applications to information retrieval"
    - "practical entropy compressed rank select dictionary"

Connected through hyperedge HE-2 (induced by source paper "fmtree a fast locating algorithm of fm indexes for genomic data"):
  with members:
    - "optimal seed solver optimizing seed selection in read mapping"

Connected through hyperedge HE-3 (induced by source paper "csa fast pattern search for large alphabets"):
  with members:
    - "from theory to practice plug and play with succinct data structures"
    - "practical entropy compressed rank select dictionary"

Connected through hyperedge HE-4 (induced by source paper "relative compressed suffix trees"):
  with members:
    - "indexing variation graphs"
    - "rlzap relative lempel ziv with adaptive pointers"
    - "composite repetition aware data structures"
    - "searching and indexing genomic databases via kernelization"
    - "from theory to practice plug and play with succinct data structures"
    - "fixed block compression boosting in fm indexes"
    - "a faster grammar based self index"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"

Connected through hyperedge HE-5 (induced by source paper "fm index for dummies"):
  with members:
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "two simple full text indexes based on the suffix array"
    - "sampling the suffix array with minimizers"
    - "fixed block compression boosting in fm indexes"

Connected through hyperedge HE-6 (induced by source paper "full text and keyword indexes for string searching"):
  with members:
    - "the k mismatch problem revisited"
    - "a practical index for approximate dictionary matching with few mismatches"
    - "new tabulation and sparse dynamic programming based techniques for sequence similarity problems"
    - "from theory to practice plug and play with succinct data structures"

Connected through hyperedge HE-7 (induced by source paper "two simple full text indexes based on the suffix array"):
  with members:
    - "alphabet dependent string searching with wexponential search trees"
    - "large scale pattern search using reduced space on disk suffix arrays"
    - "fixed block compression boosting in fm indexes"

Connected through hyperedge HE-8 (induced by source paper "sampling the suffix array with minimizers"):
  with members:
    - "kmc 2 fast and resource frugal k mer counting"
    - "approximating lz77 via small space multiple pattern matching"
    - "two simple full text indexes based on the suffix array"

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)