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: "parallel correctness and transferability for conjunctive queries"
  Abstract: A dominant cost for query evaluation in modern massively distributed systems is the number of communication rounds. For this reason, there is a growing interest in single-round multiway join algorithms where data is first reshuffled over many servers and then evaluated in a parallel but communication-free way. The reshuffling itself is specified as a distribution policy. We introduce a correctness condition, called parallel-correctness, for the evaluation of queries w.r.t. a distribution policy. We study the complexity of parallel-correctness for conjunctive queries as well as transferability of parallel-correctness between queries. We also investigate the complexity of transferability for certain families of distribution policies, including, for instance, the Hypercube distribution.

Connected through hyperedge HE-1 (induced by source paper "a case for stale synchronous distributed model for declarative recursive computation"):
  with members:
    - "scaling up reasoning and advanced analytics on bigdata"
    - "effective techniques for message reduction and load balancing in distributed graph computation"
    - "a datalog based computational model for coordination free data parallel systems"
    - "relational transducers for declarative networking"

Connected through hyperedge HE-2 (induced by source paper "split correctness in information extraction"):
  with members:
    - "constant delay algorithms for regular document spanners"
    - "document spanners for extracting incomplete information expressiveness and complexity"
    - "joining extractions of regular expressions"
    - "neural architectures for named entity recognition"
    - "incremental knowledge base construction using deepdive"
    - "named entity recognition with bidirectional lstm cnns"
    - "distributed xml design"
    - "a sentimental education sentiment analysis using subjectivity summarization based on minimum cuts"

Connected through hyperedge HE-3 (induced by source paper "efficient and private approximations of distributed databases calculations"):
  with members:
    - "a minimal variance estimator for the cardinality of big data set intersection"
    - "when distributed computation is communication expensive"
    - "calibrating data to sensitivity in private data analysis"
    - "what you can do with coordinated samples"
    - "coordinated weighted sampling for estimating aggregates over multiple weight assignments"
    - "explicit learning curves for transduction and application to clustering and compression algorithms"

Connected through hyperedge HE-4 (induced by source paper "parallel correctness and containment for conjunctive queries with union and negation"):
  with members:
    - "skew in parallel query processing"
    - "communication steps for parallel query processing"
    - "win move is coordination free sometimes"
    - "shark sql and rich analytics at scale"
    - "relational transducers for declarative networking"

Connected through hyperedge HE-5 (induced by source paper "a datalog based computational model for coordination free data parallel systems"):
  with members:
    - "on the calm principle for bulk synchronous parallel computation"
    - "blazes coordination analysis for distributed programs"
    - "win move is coordination free sometimes"
    - "relational transducers for declarative networking"

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)