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 "wsd algorithm based on a new method of vector word contexts proximity calculation via epsilon filtration"):
  Abstract: The problem of word sense disambiguation (WSD) is considered in the article. Given a set of synonyms (synsets) and sentences with these synonyms. It is necessary to select the meaning of the word in the sentence automatically. 1285 sentences were tagged by experts, namely, one of the dictionary meanings was selected by experts for target words. To solve the WSD-problem, an algorithm based on a new method of vector-word contexts proximity calculation is proposed. In order to achieve higher accuracy, a preliminary epsilon-filtering of words is performed, both in the sentence and in the set of synonyms. An extensive program of experiments was carried out. Four algorithms are implemented, including a new algorithm. Experiments have shown that in a number of cases the new algorithm shows better results. The developed software and the tagged corpus have an open license and are available online. Wiktionary and Wikisource are used. A brief description of this work can be viewed in slides (this https URL). Video lecture in Russian on this research is available online (this https URL).

Includes members:
  Member "calculated attributes of synonym sets":
    also connected through other hyperedges:
      (none)
  Member "linking imagenet wordnet synsets with wikidata":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "wikidata from a research perspective a systematic mapping study of wikidata")
  Member "analysis of wikipedia based corpora for question answering":
    also connected through other hyperedges:
      (none)
  Member "texts in meaning out neural language models in semantic similarity task for russian":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distributional semantic modeling a revised technique to train term word vector space models applying the ontology related approach")

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)