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 "roget s thesaurus as a lexical resource for natural language processing"):
  Abstract: WordNet proved that it is possible to construct a large-scale electronic lexical database on the principles of lexical semantics. It has been accepted and used extensively by computational linguists ever since it was released. Inspired by WordNet's success, we propose as an alternative a similar resource, based on the 1987 Penguin edition of Roget's Thesaurus of English Words and Phrases. #R##N#Peter Mark Roget published his first Thesaurus over 150 years ago. Countless writers, orators and students of the English language have used it. Computational linguists have employed Roget's for almost 50 years in Natural Language Processing, however hesitated in accepting Roget's Thesaurus because a proper machine tractable version was not available. #R##N#This dissertation presents an implementation of a machine-tractable version of the 1987 Penguin edition of Roget's Thesaurus - the first implementation of its kind to use an entire current edition. It explains the steps necessary for taking a machine-readable file and transforming it into a tractable system. This involves converting the lexical material into a format that can be more easily exploited, identifying data structures and designing classes to computerize the Thesaurus. Roget's organization is studied in detail and contrasted with WordNet's. #R##N#We show two applications of the computerized Thesaurus: computing semantic similarity between words and phrases, and building lexical chains in a text. The experiments are performed using well-known benchmarks and the results are compared to those of other systems that use Roget's, WordNet and statistical techniques. Roget's has turned out to be an excellent resource for measuring semantic similarity; lexical chains are easily built but more difficult to evaluate. We also explain ways in which Roget's Thesaurus and WordNet can be combined.

Includes members:
  Member "not as easy as it seems automating the construction of lexical chains using roget s thesaurus":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "keyphrase extraction enhancing lists")
  Member "roget s thesaurus and semantic similarity":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "from word to sense embeddings a survey on vector representations of meaning")

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)