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: "graphchi db simple design for a scalable graph database system on just a pc"
  Abstract: We propose a new data structure, Parallel Adjacency Lists (PAL), for efficiently managing graphs with billions of edges on disk. The PAL structure is based on the graph storage model of GraphChi (Kyrola et. al., OSDI 2012), but we extend it to enable online database features such as queries and fast insertions. In addition, we extend the model with edge and vertex attributes. Compared to previous data structures, PAL can store graphs more compactly while allowing fast access to both the incoming and the outgoing edges of a vertex, without duplicating data. Based on PAL, we design a graph database management system, GraphChi-DB, which can also execute powerful analytical graph computation. #R##N#We evaluate our design experimentally and demonstrate that GraphChi-DB achieves state-of-the-art performance on graphs that are much larger than the available memory. GraphChi-DB enables anyone with just a laptop or a PC to work with extremely large graphs.

Connected through hyperedge HE-1 (induced by source paper "weaver a high performance transactional graph database based on refinable timestamps"):
  with members:
    - "effective techniques for message reduction and load balancing in distributed graph computation"
    - "warp lightweight multi key transactions for key value stores"
    - "robobrain large scale knowledge engine for robots"
    - "pregelix big ger graph analytics on a dataflow engine"
    - "rethinking serializable multiversion concurrency control"
    - "the anatomy of the facebook social graph"

Connected through hyperedge HE-2 (induced by source paper "a survey on methods and systems for graph compression"):
  with members:
    - "preach a fast lightweight reachability index using pruning and contraction hierarchies"
    - "scalable rdf data compression using x10"
    - "dagger a scalable index for reachability queries in large dynamic graphs"
    - "graphlab a new framework for parallel machine learning"

Connected through hyperedge HE-3 (induced by source paper "graphite an extensible graph traversal framework for relational database management systems"):
  with members:
    - "parallel breadth first search on distributed memory systems"
    - "a path algebra for multi relational graphs"
    - "constructions from dots and lines"

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)