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: "efficient and compact representations of some non canonical prefix free codes"
  Abstract: For many kinds of prefix-free codes there are efficient and compact alternatives to the traditional tree-based representation. Since these put the codes into canonical form, however, they can only be used when we can choose the order in which codewords are assigned to characters. In this paper we first show how, given a probability distribution over an alphabet of \(\sigma \) characters, we can store a nearly optimal alphabetic prefix-free code in \(o (\sigma )\) bits such that we can encode and decode any character in constant time. We then consider a kind of code introduced recently to reduce the space usage of wavelet matrices (Claude, Navarro, and Ordonez, Information Systems, 2015). They showed how to build an optimal prefix-free code such that the codewords’ lengths are non-decreasing when they are arranged such that their reverses are in lexicographic order. We show how to store such a code in \(\mathcal {O}\!\left( {\sigma \log L + 2^{\epsilon L}}\right) \) bits, where L is the maximum codeword length and \(\epsilon \) is any positive constant, such that we can encode and decode any character in constant time under reasonable assumptions. Otherwise, we can always encode and decode a codeword of \(\ell \) bits in time \(\mathcal {O}\!\left( {\ell }\right) \) using \(\mathcal {O}\!\left( {\sigma \log L}\right) \) bits of space.

Connected through hyperedge HE-1 (induced by source paper "about birds project bioinformatics and information retrieval data structures analysis and design"):
  with members:
    - "compact representations of event sequences"
    - "parallel construction of wavelet trees on multicore architectures"
    - "run compressed rank select for large alphabets"
    - "efficient compression and indexing of trajectories"
    - "grammar compressed sequences with rank select support"
    - "compressed representation of dynamic binary relations with applications"
    - "a succinct data structure for self indexing ternary relations"
    - "aggregated 2d range queries on clustered points"

Connected through hyperedge HE-2 (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"
    - "on compressing permutations and adaptive sorting"
    - "new algorithms on wavelet trees and applications to information retrieval"
    - "compressed text indexes from theory to practice"
    - "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)