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 "a survey of methods to ease the development of highly multilingual text mining applications"):
  Abstract: Multilingual text processing is useful because the information content found in different languages is complementary, both regarding facts and opinions. While Information Extraction and other text mining software can, in principle, be developed for many languages, most text analysis tools have only been applied to small sets of languages because the development effort per language is large. Self-training tools obviously alleviate the problem, but even the effort of providing training data and of manually tuning the results is usually considerable. In this paper, we gather insights by various multilingual system developers on how to minimise the effort of developing natural language processing applications for many languages. We also explain the main guidelines underlying our own effort to develop complex text mining software for tens of languages. While these guidelines--most of all: extreme simplicity--can be very restrictive and limiting, we believe to have shown the feasibility of the approach through the development of the Europe Media Monitor (EMM) family of applications ( http://emm.newsbrief.eu/overview.html ). EMM is a set of complex media monitoring tools that process and analyse up to 100,000 online news articles per day in between twenty and fifty languages. We will also touch upon the kind of language resources that would make it easier for all to develop highly multilingual text mining applications. We will argue that--to achieve this--the most needed resources would be freely available, simple, parallel and uniform multilingual dictionaries, corpora and software tools.

Includes members:
  Member "sentiment analysis in the news":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a system for the 2019 sentiment emotion and cognitive state task of darpas lorelei project")
  Member "an introduction to the europe media monitor family of applications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a pragmatic guide to geoparsing evaluation")
  Member "extending an information extraction tool set to central and eastern european languages":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "navigating multilingual news collections using automatically extracted information")
  Member "the jrc acquis a multilingual aligned parallel corpus with 20 languages":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "augmenting neural machine translation with knowledge graphs")

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.CL(Computation and Language)