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: "an idea an ingestion framework for data enrichment in asterixdb"
  Abstract: Big Data today is being generated at an unprecedented rate from various sources such as sensors, applications, and devices, and it often needs to be enriched based on other existing information to support complex analytical queries. Depending on the use case, the enrichment operations can be compiled code, declarative queries, or machine learning models with different complexities. For enrichments that will be frequently used in the future, it can be advantageous to push their computation into the ingestion pipeline so that they can be stored (and queried) together with the data. In some cases, the referenced information may change over time, so the ingestion pipeline should be able to adapt to such changes to guarantee the currency and/or correctness of the enrichment results. In this paper, we present a new data ingestion framework that supports data ingestion at scale, enrichments requiring complex operations, and adaptiveness to reference data changes. We explain how this framework has been built on top of Apache AsterixDB and investigate its performance at scale under various workloads.

Connected through hyperedge HE-1 (induced by source paper "bad to the bone big active data at its core"):
  with members:
    - "efficient data ingestion and query processing for lsm based storage systems"
    - "planetsense a real time streaming and spatio temporal analytics platform for gathering geo spatial intelligence from open source data"
    - "asterixdb a scalable open source bdms"
    - "linview incremental view maintenance for complex analytical queries"

Connected through hyperedge HE-2 (induced by source paper "on performance stability in lsm based storage systems extended version"):
  with members:
    - "lsm based storage techniques a survey"
    - "efficient data ingestion and query processing for lsm based storage systems"
    - "enabling efficient updates in kv storage via hashing design and performance evaluation"
    - "asterixdb a scalable open source bdms"

Connected through hyperedge HE-3 (induced by source paper "ingesting high velocity streaming graphs from social media sources"):
  with members:
    - "a survey on graph processing accelerators challenges and opportunities"
    - "graphchallenge org raising the bar on graph analytic performance"
    - "an experimental survey on big data frameworks"

Connected through hyperedge HE-4 (induced by source paper "progressive evaluation of queries over untagged data"):
  with members:
    - "verdictdb universalizing approximate query processing"
    - "sampling based query re optimization"
    - "meta des"
    - "exploiting correlations for expensive predicate evaluation"

Connected through hyperedge HE-5 (induced by source paper "pique progressive integrated query operator with pay as you go enrichment"):
  with members:
    - "exploiting correlations for expensive predicate evaluation"

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)