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: "a linear time algorithm for seeds computation"
  Abstract: A seed in a word is a relaxed version of a period in which the occurrences of the repeating subword may overlap. We show a linear-time algorithm computing a linear-size representation of all the seeds of a word (the number of seeds might be quadratic). In particular, one can easily derive the shortest seed and the number of seeds from our representation. Thus, we solve an open problem stated in the survey by Smyth (2000) and improve upon a previous O(n log n) algorithm by Iliopoulos, Moore, and Park (1996). Our approach is based on combinatorial relations between seeds and subword complexity (used here for the first time in context of seeds). In the previous papers, the compact representation of seeds consisted of two independent parts operating on the suffix tree of the word and the suffix tree of the reverse of the word, respectively. Our second contribution is a simpler representation of all seeds which avoids dealing with the reversed word. #R##N#A preliminary version of this work, with a much more complex algorithm constructing the earlier representation of seeds, was presented at the 23rd Annual ACM-SIAM Symposium of Discrete Algorithms (SODA 2012).

Connected through hyperedge HE-1 (induced by source paper "internal dictionary matching"):
  with members:
    - "computing all distinct squares in linear time for integer alphabets"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"
    - "wavelet trees meet suffix trees"
    - "internal pattern matching queries in a text and applications"
    - "recompression a simple and powerful technique for word equations"
    - "faster fully compressed pattern matching by recompression"

Connected through hyperedge HE-2 (induced by source paper "experimental evaluation of algorithms for computing quasiperiods"):
  with members:
    - "indexing weighted sequences neat and efficient"
    - "two strings at hamming distance 1 cannot be both quasiperiodic"
    - "efficient index for weighted sequences"
    - "computing covers using prefix tables"
    - "covering problems for partial words and for indeterminate strings"

Connected through hyperedge HE-3 (induced by source paper "on longest common property preserved substring queries"):
  with members:
    - "longest property preserved common factor"
    - "minimal suffix and rotation of a substring in optimal time"
    - "computing all distinct squares in linear time for integer alphabets"

Connected through hyperedge HE-4 (induced by source paper "indexing weighted sequences neat and efficient"):
  with members:
    - "pattern matching and consensus problems on weighted sequences and profiles"
    - "efficient index for weighted sequences"
    - "probabilistic threshold indexing for uncertain strings"
    - "fast average case pattern matching on weighted sequences"
    - "weighted ancestors in suffix trees"

Connected through hyperedge HE-5 (induced by source paper "range predecessor and lempel ziv parsing"):
  with members:
    - "faster lightweight lempel ziv parsing"
    - "wavelet trees meet suffix trees"
    - "linear time construction of compressed text indices in compact space"
    - "queries on lz bounded encodings"
    - "lightweight lempel ziv parsing"
    - "faster compact on line lempel ziv factorization"
    - "linear time lempel ziv factorization simple fast small"
    - "succinct indices for range queries with applications to orthogonal range maxima"

Connected through hyperedge HE-6 (induced by source paper "lempel ziv computation in small space lz ciss"):
  with members:
    - "alphabet dependent string searching with wexponential search trees"
    - "simpler and faster lempel ziv factorization"
    - "fully functional static and dynamic succinct trees"
    - "optimal succinctness for range minimum queries"

Connected through hyperedge HE-7 (induced by source paper "covering problems for partial words and for indeterminate strings"):
  with members:
    - "computing covers using prefix tables"

Connected through hyperedge HE-8 (induced by source paper "fast algorithm for partial covers in words"):
  with members:
    - "cross document pattern matching"

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)