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: "incrementally maintaining classification using an rdbms"
  Abstract: The proliferation of imprecise data has motivated both researchers and the database industry to push statistical techniques into relational database management systems (RDBMSs). We study algorithms to maintain model-based views for a popular statistical technique, classification, inside an RDBMS in the presence of updates to the training examples. We make three technical contributions: (1) An algorithm that incrementally maintains classification inside an RDBMS. (2) An analysis of the above algorithm that shows that our algorithm is optimal among all deterministic algorithms (and asymptotically within a factor of 2 of a nondeterministic optimal). (3) An index structure based on the technical ideas that underlie the above algorithm which allows us to store only a fraction of the entities in memory. We apply our techniques to text processing, and we demonstrate that our algorithms provide several orders of magnitude improvement over non-incremental approaches to classification on a variety of data sets: such as the Cora, UCI Machine Learning Repository data sets, Citeseer, and DBLife.

Connected through hyperedge HE-1 (induced by source paper "incremental knowledge base construction using deepdive"):
  with members:
    - "from data fusion to knowledge fusion"
    - "logarithmic time updates and queries in probabilistic networks"
    - "feature engineering for knowledge base construction"
    - "errata distant supervision for relation extraction with matrix completion"
    - "linview incremental view maintenance for complex analytical queries"
    - "dimmwitted a study of main memory statistical analytics"
    - "a convolutional neural network for modelling sentences"
    - "adaptive inference on general graphical models"

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)