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: "fast and tiny structural self indexes for xml"
  Abstract: XML document markup is highly repetitive and therefore well compressible using dictionary-based methods such as DAGs or grammars. In the context of selectivity estimation, grammar-compressed trees were used before as synopsis for structural XPath queries. Here a fully-fledged index over such grammars is presented. The index allows to execute arbitrary tree algorithms with a slow-down that is comparable to the space improvement. More interestingly, certain algorithms execute much faster over the index (because no decompression occurs). E.g., for structural XPath count queries, evaluating over the index is faster than previous XPath implementations, often by two orders of magnitude. The index also allows to serialize XML results (including texts) faster than previous systems, by a factor of ca. 2-3. This is due to efficient copy handling of grammar repetitions, and because materialization is totally avoided. In order to compare with twig join implementations, we implemented a materializer which writes out pre-order numbers of result nodes, and show its competitiveness.

Connected through hyperedge HE-1 (induced by source paper "constant delay traversal of grammar compressed graphs with bounded rank"):
  with members:
    - "balancing straight line programs"
    - "grammar based graph compression"
    - "fully functional static and dynamic succinct trees"

Connected through hyperedge HE-2 (induced by source paper "grammar based graph compression"):
  with members:
    - "a succinct data structure for self indexing ternary relations"
    - "traversing grammar compressed trees with constant delay"
    - "compressed tree canonization"
    - "recompression a simple and powerful technique for word equations"
    - "structure induction by lossless graph compression"
    - "approximation algorithms for pspace hard hierarchically and periodically specified problems"
    - "identifying hierarchical structure in sequences a linear time algorithm"

Connected through hyperedge HE-3 (induced by source paper "traversing grammar compressed trees with constant delay"):
  with members:
    - "tree compression with top trees revisited"
    - "constructing small tree grammars and small circuits for formulas"
    - "xpath node selection over grammar compressed trees"
    - "approximation of smallest linear tree grammar"
    - "faster fully compressed pattern matching by recompression"
    - "fully functional static and dynamic succinct trees"

Connected through hyperedge HE-4 (induced by source paper "xml compression via dags"):
  with members:
    - "fdb a query engine for factorised relational databases"
    - "random access to grammar compressed strings"
    - "identifying hierarchical structure in sequences a linear time algorithm"

Connected through hyperedge HE-5 (induced by source paper "xpath node selection over grammar compressed trees"):
  with members:
    - "xpath whole query optimization"

Connected through hyperedge HE-6 (induced by source paper "fast in memory xpath search over compressed text and tree indexes"):
  with members:
    - "xpath whole query optimization"
    - "fully functional static and dynamic succinct trees"
    - "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.DB(Databases)