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: "cram compressed random access memory"
  Abstract: We present a new data structure called the \emph{Compressed Random Access Memory} (CRAM) that can store a dynamic string $T$ of characters, e.g., representing the memory of a computer, in compressed form while achieving asymptotically almost-optimal bounds (in terms of empirical entropy) on the compression ratio. It allows short substrings of $T$ to be decompressed and retrieved efficiently and, significantly, characters at arbitrary positions of $T$ to be modified quickly during execution \emph{without decompressing the entire string}. This can be regarded as a new type of data compression that can update a compressed file directly. Moreover, at the cost of slightly increasing the time spent per operation, the CRAM can be extended to also support insertions and deletions. Our key observation that the empirical entropy of a string does not change much after a small change to the string, as well as our simple yet efficient method for maintaining an array of variable-length blocks under length modifications, may be useful for many other applications as well.

Connected through hyperedge HE-1 (induced by source paper "local decode and update for big data compression"):
  with members:
    - "how to store a random walk"
    - "set membership with non adaptive bit probes"
    - "compressed data structures for dynamic sequences"
    - "set membership with a few bit probes"
    - "bounds on the parameters of locally recoverable codes"
    - "a family of optimal locally recoverable codes"
    - "update efficiency and local repairability limits for capacity approaching codes"
    - "on locally decodable source coding"

Connected through hyperedge HE-2 (induced by source paper "towards better compressed representations"):
  with members:
    - "entropy bounds for grammar compression"
    - "optimal dynamic sequence representations"

Connected through hyperedge HE-3 (induced by source paper "m bonsai a practical compact dynamic trie"):
  with members:
    - "from theory to practice plug and play with succinct data structures"
    - "one variable word equations in linear time"
    - "the wavelet trie maintaining an indexed sequence of strings in compressed space"

Connected through hyperedge HE-4 (induced by source paper "compressed data structures for dynamic sequences"):
  with members:
    - "on line indexing for general alphabets via predecessor queries on subsets of an ordered list"
    - "optimal dynamic sequence representations"
    - "new lower and upper bounds for representing sequences"
    - "succinct representations of permutations and functions"
    - "succinct representations of dynamic strings"
    - "fully functional static and dynamic succinct trees"

Connected through hyperedge HE-5 (induced by source paper "a succinct grammar compression"):
  with members:
    - "compressed representations of permutations and applications"
    - "practical entropy compressed rank select dictionary"

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)