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: "simple schemas for unordered xml"
  Abstract: We consider unordered XML, where the relative order among siblings is ignored, and propose two simple yet practical schema formalisms: disjunctive multiplicity schemas (DMS), and its restriction, disjunction-free multiplicity schemas (MS). We investigate their computational properties and characterize the complexity of the following static analysis problems: schema satisfiability, membership of a tree to the language of a schema, schema containment, twig query satisfiability, implication, and containment in the presence of schema. Our research indicates that the proposed formalisms retain much of the expressiveness of DTDs without an increase in computational complexity.

Connected through hyperedge HE-1 (induced by source paper "an effective algorithm for learning single occurrence regular expressions with interleaving"):
  with members:
    - "practical study of deterministic regular expressions from large scale xml and schema data"
    - "discovering restricted regular expressions with interleaving"
    - "learning schemas for unordered xml"
    - "learning deterministic regular expressions for the inference of schemas from xml data"

Connected through hyperedge HE-2 (induced by source paper "learning restricted regular expressions with interleaving"):
  with members:
    - "discovering restricted regular expressions with interleaving"
    - "learning schemas for unordered xml"
    - "schema based scheduling of event processors and buffer minimization for queries on structured data streams"

Connected through hyperedge HE-3 (induced by source paper "schemas for unordered xml on a dime"):
  with members:
    - "validating rdf with shape expressions"
    - "learning schemas for unordered xml"
    - "on the complexity of xpath containment in the presence of disjunction dtds and variables"

Connected through hyperedge HE-4 (induced by source paper "discovering restricted regular expressions with interleaving"):
  with members:
    - "schemas for unordered xml on a dime"
    - "learning schemas for unordered xml"
    - "learning deterministic regular expressions for the inference of schemas from xml data"

Connected through hyperedge HE-5 (induced by source paper "validating rdf with shape expressions"):
  with members:
    - "schemas for unordered xml on a dime"

Connected through hyperedge HE-6 (induced by source paper "learning schemas for unordered xml"):
  with members:
    - "learning deterministic regular expressions for the inference of schemas from xml data"

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)