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: "efficient approximation of well designed sparql queries"
  Abstract: Query response time often influences user experience in the real world. However, it possibly takes more time to answer a query with its all exact solutions, especially when it contains the OPT operations since the OPT operation is the least conventional operator in SPARQL. So it becomes essential to make a trade-off between the query response time and the accuracy of their solutions. In this paper, based on the depth of the OPT operation occurring in a query, we propose an approach to obtain its all approximate queries with less depth of the OPT operation. This paper mainly discusses those queries with well-designed patterns since the OPT operation in a well-designed pattern is really "optional". Firstly, we transform a well-designed pattern in OPT normal form into a well-designed tree, whose inner nodes are labeled by OPT operation and leaf nodes are labeled by patterns containing other operations such as the AND operation and the FILTER operation. Secondly, based on this well-designed tree, we remove "optional" well-designed subtrees with less depth of the OPT operation and then obtain approximate queries with different depths of the OPT operation. Finally, we evaluate the approximate query efficiency with the degree of approximation.

Connected through hyperedge HE-1 (induced by source paper "piwd a plugin based framework for well designed sparql"):
  with members:
    - "on the statistical analysis of practical sparql queries"
    - "left bit right for sparql join queries with optional patterns left outer joins"
    - "context free path queries on rdf graphs"
    - "processing sparql queries over distributed rdf graphs"
    - "on the satisfiability problem for sparql patterns"
    - "efficient subgraph matching on billion node graphs"
    - "foundations of sparql query optimization"
    - "semantics and complexity of sparql"

Connected through hyperedge HE-2 (induced by source paper "on the statistical analysis of practical sparql queries"):
  with members:
    - "on the satisfiability problem for sparql patterns"
    - "an empirical study of real world sparql queries"
    - "foundations of sparql query optimization"
    - "semantics and complexity of sparql"

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)