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: "the graph traversal pattern"
  Abstract: A graph is a structure composed of a set of vertices (i.e.nodes, dots) connected to one another by a set of edges (i.e.links, lines). The concept of a graph has been around since the late 19$^\text{th}$ century, however, only in recent decades has there been a strong resurgence in both theoretical and applied graph research in mathematics, physics, and computer science. In applied computing, since the late 1960s, the interlinked table structure of the relational database has been the predominant information storage and retrieval model. With the growth of graph/network-based data and the need to efficiently process such data, new data management systems have been developed. In contrast to the index-intensive, set-theoretic operations of relational databases, graph databases make use of index-free, local traversals. This article discusses the graph traversal pattern and its use in computing.

Connected through hyperedge HE-1 (induced by source paper "towards an integrated graph algebra for graph pattern matching with gremlin extended version"):
  with members:
    - "a stitch in time saves nine sparql querying of property graphs using gremlin traversals"
    - "the multiset semantics of sparql patterns"
    - "foundations of modern query languages for graph databases"
    - "the gremlin graph traversal machine and language invited talk"
    - "a path algebra for multi relational graphs"
    - "foundations of sparql query optimization"
    - "semantics and complexity of sparql"

Connected through hyperedge HE-2 (induced by source paper "a stitch in time saves nine sparql querying of property graphs using gremlin traversals"):
  with members:
    - "killing two birds with one stone querying property graphs using sparql via gremlinator"
    - "the multiset semantics of sparql patterns"
    - "a formal graph model for rdf and its implementation"
    - "the gremlin graph traversal machine and language invited talk"
    - "foundations of sparql query optimization"
    - "sp2bench a sparql performance benchmark"
    - "semantics and complexity of sparql"

Connected through hyperedge HE-3 (induced by source paper "v1 a visual query language for property graphs"):
  with members:
    - "property graph type system and data definition language"
    - "the gremlin graph traversal machine and language invited talk"

Connected through hyperedge HE-4 (induced by source paper "formalising opencypher graph queries in relational algebra"):
  with members:
    - "the gremlin graph traversal machine and language invited talk"
    - "semantics and complexity of sparql"

Connected through hyperedge HE-5 (induced by source paper "taper query aware partition enhancement for large heterogenous graphs"):
  with members:
    - "provgen generating synthetic prov graphs with predictable structure"
    - "multi scale community detection using stability optimisation within greedy algorithms"

Connected through hyperedge HE-6 (induced by source paper "gradoop scalable graph data management and analytics with hadoop"):
  with members:
    - "constructions from dots and lines"

Connected through hyperedge HE-7 (induced by source paper "partitioning graph databases a quantitative evaluation"):
  with members:
    - "constructions from dots and lines"
    - "divide and conquer partitioning online social networks"
    - "a local clustering algorithm for massive graphs and its application to nearly linear time graph partitioning"

Connected through hyperedge HE-8 (induced by source paper "constructions from dots and lines"):
  with members:
    - "exposing multi relational networks to single relational network analysis algorithms"
    - "faith in the algorithm part 2 computational eudaemonics"

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)