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: "linear time computation of minimal absent words using suffix array"
  Abstract: An absent word of a word y of length n is a word that does not occur in y. It is a minimal absent word if all its proper factors occur in y. Minimal absent words have been computed in genomes of organisms from all domains of life; their computation provides a fast alternative for measuring approximation in sequence comparison. There exists an O(n)-time and O(n)-space algorithm for computing all minimal absent words on a fixed-sized alphabet based on the construction of suffix automata (Crochemore et al., 1998). No implementation of this algorithm is publicly available. There also exists an O(n^2)-time and O(n)-space algorithm for the same problem based on the construction of suffix arrays (Pinho et al., 2009). An implementation of this algorithm was also provided by the authors and is currently the fastest available. In this article, we bridge this unpleasant gap by presenting an O(n)-time and O(n)-space algorithm for computing all minimal absent words based on the construction of suffix arrays. Experimental results using real and synthetic data show that the respective implementation outperforms the one by Pinho et al.

Connected through hyperedge HE-1 (induced by source paper "minimal absent words in rooted and unrooted trees"):
  with members:
    - "suffix trees dawgs and cdawgs for forward and backward tries"
    - "alignment free sequence comparison using absent words"
    - "minimal forbidden factors of circular words"
    - "a framework for space efficient string kernels"

Connected through hyperedge HE-2 (induced by source paper "constructing antidictionaries in output sensitive space"):
  with members:
    - "alignment free sequence comparison using absent words"

Connected through hyperedge HE-3 (induced by source paper "alignment free sequence comparison using absent words"):
  with members:
    - "indexing weighted sequences neat and efficient"
    - "minimal forbidden factors of circular words"
    - "linear time sequence comparison using minimal absent words applications"
    - "inducing the lcp array"

Connected through hyperedge HE-4 (induced by source paper "minimal forbidden factors of circular words"):
  with members:
    - "alignment free sequence comparison using absent words"
    - "the sequence of open and closed prefixes of a sturmian word"
    - "linear time sequence comparison using minimal absent words applications"

Connected through hyperedge HE-5 (induced by source paper "linear time string indexing and analysis in small space"):
  with members:
    - "string synchronizing sets sublinear time bwt construction and optimal lce data structure"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "a framework for space efficient string kernels"
    - "linear time construction of compressed text indices in compact space"
    - "optimal dynamic sequence representations"
    - "combined data structure for previous and next smaller values"
    - "more haste less waste lowering the redundancy in fully indexable dictionaries"
    - "optimal succinctness for range minimum queries"

Connected through hyperedge HE-6 (induced by source paper "optimal computation of avoided words"):
  with members:
    - "space efficient detection of unusual words"
    - "weighted ancestors in suffix trees"

Connected through hyperedge HE-7 (induced by source paper "linear time sequence comparison using minimal absent words applications"):
  with members:
    - "inducing the lcp 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)