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 "fast record linkage for company entities"):
  Abstract: Record Linkage is an essential part of almost all real-world systems that consume data coming from different sources, structured and unstructured. Typically no common key is available in order to connect the records. Often massive data cleaning and data integration processes have to be completed before any data analytics and further processing can be performed. Though record linkage is often seen as a somewhat tedious necessary step, it is able to reveal valuable insights of the data at hand. These insights guide further analytic approaches over the data and support data visualization. In this work we focus on company entity matching, where company name, location and industry are taken into account. The matching is done on the fly to accommodate realtime processing of streamed data. Our contribution is a system that uses rule-based matching algorithms for scoring operations which we extend with a machine learning approach to account for short company names. We propose an end-to-end highly scalable enterprise-grade system. Linkage time is greatly reduced by efficient decomposition of the search space using MinHash. High linkage accuracy is reached by the proposed thorough scoring process of the matching candidates. Based on two real world ground truth datasets, we show that our approach reaches a recall of 91% compared to 86% for baseline approaches. These results are achieved while scaling linearly with the number of nodes used in the system.

Includes members:
  Member "superminhash a new minwise hashing algorithm for jaccard similarity estimation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "probminhash a class of locality sensitive hash algorithms for the probability jaccard similarity")
  Member "bidirectional lstm crf models for sequence tagging":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dense dilated convolutions merging network for land cover classification")

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)