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: "constructions from dots and lines"
  Abstract: A graph is a data structure composed of dots (i.e. vertices) and lines (i.e. edges). The dots and lines of a graph can be organized into intricate arrangements. The ability for a graph to denote objects and their relationships to one another allow for a surprisingly large number of things to be modeled as a graph. From the dependencies that link software packages to the wood beams that provide the framing to a house, most anything has a corresponding graph representation. However, just because it is possible to represent something as a graph does not necessarily mean that its graph representation will be useful. If a modeler can leverage the plethora of tools and algorithms that store and process graphs, then such a mapping is worthwhile. This article explores the world of graphs in computing and exposes situations in which graphical models are beneficial.

Connected through hyperedge HE-1 (induced by source paper "algebraic property graphs"):
  with members:
    - "deciding equivalence with sums and the empty type"
    - "algebraic data integration"
    - "reconciliation of rdf and property graphs"

Connected through hyperedge HE-2 (induced by source paper "property graph type system and data definition language"):
  with members:
    - "g core a core for future graph query languages"

Connected through hyperedge HE-3 (induced by source paper "an introduction to graph data management"):
  with members:
    - "g core a core for future graph query languages"
    - "foundations of modern query languages for graph databases"
    - "the gremlin graph traversal machine and language invited talk"
    - "shortest path and distance queries on road networks towards bridging theory and practice"
    - "a brief study of open source graph databases"

Connected through hyperedge HE-4 (induced by source paper "g core a core for future graph query languages"):
  with members:
    - "foundations of modern query languages for graph databases"
    - "semantics and complexity of sparql"

Connected through hyperedge HE-5 (induced by source paper "grad on graph database modeling"):
  with members:
    - "efficient subgraph matching on billion node graphs"
    - "inferring networks of diffusion and influence"

Connected through hyperedge HE-6 (induced by source paper "gradoop scalable graph data management and analytics with hadoop"):
  with members:
    - "the graph traversal pattern"

Connected through hyperedge HE-7 (induced by source paper "graphite an extensible graph traversal framework for relational database management systems"):
  with members:
    - "graphchi db simple design for a scalable graph database system on just a pc"
    - "parallel breadth first search on distributed memory systems"
    - "a path algebra for multi relational graphs"

Connected through hyperedge HE-8 (induced by source paper "partitioning graph databases a quantitative evaluation"):
  with members:
    - "the graph traversal pattern"
    - "divide and conquer partitioning online social networks"
    - "a local clustering algorithm for massive graphs and its application to nearly linear time graph partitioning"

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)