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 "on extracting data from tables that are encoded using html"):
  Abstract: Tables are a common means to display data in human-friendly formats. Many authors have worked on proposals to extract those data back since this has many interesting applications. In this article, we summarise and compare many of the proposals to extract data from tables that are encoded using HTML and have been published between $2000$ and $2018$. We first present a vocabulary that homogenises the terminology used in this field; next, we use it to summarise the proposals; finally, we compare them side by side. Our analysis highlights several challenges to which no proposal provides a conclusive solution and a few more that have not been addressed sufficiently; simply put, no proposal provides a complete solution to the problem, which seems to suggest that this research field shall keep active in the near future. We have also realised that there is no consensus regarding the datasets and the methods used to evaluate the proposals, which hampers comparing the experimental results.

Includes members:
  Member "cotype joint extraction of typed entities and relations with knowledge bases":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "knowledge graphs")
  Member "learning the semantics of structured data sources":
    also connected through other hyperedges:
      (none)
  Member "identifying web tables supporting a neglected type of content on the web":
    also connected through other hyperedges:
      (none)
  Member "web data extraction applications and techniques":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "knowledge graphs")
  Member "overview of web content mining tools":
    also connected through other hyperedges:
      (none)
  Member "answering table queries on the web using column keywords":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "web table extraction retrieval and augmentation a survey")

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.IR(Information Retrieval)