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: "variable order de bruijn graphs"
  Abstract: The de Bruijn graph $G_K$ of a set of strings $S$ is a key data structure in genome assembly that represents overlaps between all the $K$-length substrings of $S$. Construction and navigation of the graph is a space and time bottleneck in practice and the main hurdle for assembling large, eukaryote genomes. This problem is compounded by the fact that state-of-the-art assemblers do not build the de Bruijn graph for a single order (value of $K$) but for multiple values of $K$. More precisely, they build $d$ de Bruijn graphs, each with a specific order, i.e., $G_{K_1}, G_{K_2}, ..., G_{K_d}$. Although, this paradigm increases the quality of the assembly produced, it increases the memory by a factor of $d$ in most cases. In this paper, we show how to augment a succinct de Bruijn graph representation by Bowe et al. (Proc. WABI, 2012) to support new operations that let us change order on the fly, effectively representing all de Bruijn graphs of order up to some maximum $K$ in a single data structure. Our experiments show our variable-order de Bruijn graph only modestly increases space usage, construction time, and navigation time compared to a single order graph.

Connected through hyperedge HE-1 (induced by source paper "fully functional bidirectional burrows wheeler indexes"):
  with members:
    - "simulating the dna string graph in succinct space"
    - "assembling omnitigs using hidden order de bruijn graphs"
    - "representing the suffix tree with the cdawg"
    - "fast label extraction in the cdawg"
    - "linear time string indexing and analysis in small space"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "linear time construction of compressed text indices in compact space"
    - "engineering small space dictionary matching"

Connected through hyperedge HE-2 (induced by source paper "lightweight merging of compressed indices based on bwt variants"):
  with members:
    - "space efficient merging of succinct de bruijn graphs"
    - "external memory bwt and lcp computation for sequence collections with applications"
    - "indexing variation graphs"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "lightweight lcp construction for very large collections of strings"
    - "burrows wheeler transform for terabases"
    - "linear time construction of compressed text indices in compact space"

Connected through hyperedge HE-3 (induced by source paper "simulating the dna string graph in succinct space"):
  with members:
    - "linear time construction of compressed text indices in compact space"
    - "from theory to practice plug and play with succinct data structures"
    - "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 "an index for sequencing reads based on the colored de bruijn graph"):
  with members:
    - "from theory to practice plug and play with succinct data structures"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"
    - "practical entropy compressed rank select dictionary"

Connected through hyperedge HE-5 (induced by source paper "data structures to represent sets of k long dna sequences"):
  with members:
    - "fast and scalable minimal perfect hashing for massive key sets"
    - "fully dynamic de bruijn graphs"
    - "don t thrash how to cache your hash on flash"

Connected through hyperedge HE-6 (induced by source paper "space efficient merging of succinct de bruijn graphs"):
  with members:
    - "lightweight merging of compressed indices based on bwt variants"
    - "external memory bwt and lcp computation for sequence collections with applications"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"

Connected through hyperedge HE-7 (induced by source paper "survey and taxonomy of lossless graph compression and space efficient graph representations"):
  with members:
    - "grammar based graph compression"
    - "compressing networks with super nodes"
    - "graphzip dictionary based compression for mining graph streams"
    - "parallel construction of compact planar embeddings"
    - "compressed representation of dynamic binary relations with applications"
    - "a succinct data structure for self indexing ternary relations"
    - "fully dynamic de bruijn graphs"
    - "compressing graphs and indexes with recursive graph bisection"

Connected through hyperedge HE-8 (induced by source paper "external memory bwt and lcp computation for sequence collections with applications"):
  with members:
    - "the colored longest common prefix array computed via sequential scans"
    - "computing the bwt and lcp array of a set of strings in external memory"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "lightweight lcp construction for very large collections of strings"
    - "an external memory algorithm for string graph construction"
    - "linear time construction of compressed text indices in compact space"
    - "lightweight data indexing and compression in external memory"

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)