human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "progressive evaluation of queries over untagged data"):
  Abstract: Modern information systems often collect raw data in the form of text, images, video, and sensor readings. Such data needs to be further interpreted/enriched prior to being analyzed. Enrichment is often a result of automated machine learning and or signal processing techniques that associate appropriate but uncertain tags with the data. Traditionally, with the notable exception of a few systems, enrichment is considered to be a separate pre-processing step performed independently prior to data analysis. Such an approach is becoming increasingly infeasible since modern data capture technologies enable creation of very large data collections for which it is computationally difficult/impossible and ultimately not beneficial to derive all tags as a preprocessing step. Hence, approaches that perform tagging at query/analysis time on the data of interest need to be considered. This paper explores the problem of joint tagging and query processing. In particular, the paper considers a scenario where tagging can be performed using several techniques that differ in cost and accuracy and develops a progressive approach to answering Select-Project-Join (SPJ) queries (with a restricted version of the join predicates) that enriches the right data to the right degree so as to maximize the quality of the query results. The experimental results show that the proposed approach performs significantly better compared to baseline approaches.

Includes members:
  Member "an idea an ingestion framework for data enrichment in asterixdb":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "bad to the bone big active data at its core")
  Member "verdictdb universalizing approximate query processing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "video monitoring queries")
  Member "sampling based query re optimization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a note on operator level query execution cost modeling")
  Member "meta des":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "dynamic deep multi modal fusion for image privacy prediction")
  Member "exploiting correlations for expensive predicate evaluation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "towards scalable dataframe systems")

Question: Please tell me which class the source paper 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)