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: "extending sparql to support entity grouping and path queries"
  Abstract: The ability to efficiently find relevant subgraphs and paths in a large graph to a given query is important in many applications including scientific data analysis, social networks, and business intelligence. Currently, there is little support and no efficient approaches for expressing and executing such queries. This paper proposes a data model and a query language to address this problem. The contributions include supporting the construction and selection of: (i) folder nodes, representing a set of related entities, and (ii) path nodes, representing a set of paths in which a path is the transitive relationship of two or more entities in the graph. Folders and paths can be stored and used for future queries. We introduce FPSPARQL which is an extension of the SPARQL supporting folder and path nodes. We have implemented a query engine that supports FPSPARQL and the evaluation results shows its viability and efficiency for querying large graph datasets.

Connected through hyperedge HE-1 (induced by source paper "curating social media data"):
  with members:
    - "how to work a crowd developing crowd capital through crowdsourcing"
    - "hollywood in homes crowdsourcing data collection for activity understanding"
    - "on the dynamics of social media popularity a youtube case study"
    - "big data and cross document coreference resolution current state and future opportunities"
    - "temporal provenance model tpm model and query language"
    - "crowder crowdsourcing entity resolution"

Connected through hyperedge HE-2 (induced by source paper "temporal provenance model tpm model and query language"):
  with members:
    - "tabletrans multitrans intertrans and treetrans diverse tools built on the annotation graph toolkit"

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)