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 comprehensive comparative study of word and sentence similarity measures"):
  Abstract: Sentence similarity is considered the basis of many natural language tasks such as information retrieval, question answering and text summarization. The semantic meaning between compared text fragments is based on the words’ semantic features and their relationships. This article reviews a set of word and sentence similarity measures and compares them on benchmark datasets. On the studied datasets, results showed that hybrid semantic measures perform better than both knowledge and corpus based measures.

Includes members:
  Member "using latent semantic analysis to identify quality in use qu indicators from user reviews":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "building a pilot software quality in use benchmark dataset")
  Member "building a pilot software quality in use benchmark dataset":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mining software quality from software reviews research trends and open issues")
  Member "measuring software quality in use state of the art and research challenges":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mining software quality from software reviews research trends and open issues")
  Member "roget s thesaurus and semantic similarity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "from word to sense embeddings a survey on vector representations of meaning")
  Member "text relatedness based on a word thesaurus":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "interactive attention for semantic text matching")
  Member "the google similarity distance":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "semantic relatedness for keyword disambiguation exploiting different embeddings")
  Member "mining the web for synonyms pmi ir versus lsa on toefl":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a review of keyphrase extraction")

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)