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 "citation recommendation approaches and datasets"):
  Abstract: Citation recommendation describes the task of recommending citations for a given text. Due to the overload of published scientific works in recent years on the one hand, and the need to cite the most appropriate publications when writing scientific texts on the other hand, citation recommendation has emerged as an important research topic. In recent years, several approaches and evaluation data sets have been presented. However, to the best of our knowledge, no literature survey has been conducted explicitly on citation recommendation. In this article, we give a thorough introduction into automatic citation recommendation research. We then present an overview of the approaches and data sets for citation recommendation and identify differences and commonalities using various dimensions. Last but not least, we shed light on the evaluation methods, and outline general challenges in the evaluation and how to meet them. We restrict ourselves to citation recommendation for scientific publications, as this document type has been studied the most in this area. However, many of the observations and discussions included in this survey are also applicable to other types of text, such as news articles and encyclopedic articles.

Includes members:
  Member "content based citation recommendation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "navigation based candidate expansion and pretrained language models for citation recommendation")
  Member "hyperdoc2vec distributed representations of hypertext documents":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hybridcite a hybrid model for context aware citation recommendation")
  Member "core elements in the process of citing publications conceptual overview of the literature":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "evaluating research and researchers by the journal impact factor is it better than coin flipping")
  Member "cross language citation recommendation via hierarchical representation learning on heterogeneous graph":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "hybridcite a hybrid model for context aware citation recommendation")
  Member "machine learning vs rules and out of the box vs retrained an evaluation of open source bibliographic reference and citation parsers":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "gorc a large contextual citation graph of academic papers")
  Member "on measuring bias in online information":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "bias in data driven ai systems an introductory survey")
  Member "all fingers are not equal intensity of references in scientific articles":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "go wide go deep quantifying the impact of scientific papers through influence dispersion trees")
  Member "finding news citations for wikipedia":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "quantifying engagement with citations on wikipedia")

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)