human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "similarity based models of word cooccurrence probabilities"
  Abstract: In many applications of natural language processing (NLP) it is necessary to determine the likelihood of a given word combination. For example, a speech recognizer may need to determine which of the two word combinations ``eat a peach'' and ``eat a beach'' is more likely. Statistical NLP methods determine the likelihood of a word combination from its frequency in a training corpus. However, the nature of language is such that many word combinations are infrequent and do not occur in any given corpus. In this work we propose a method for estimating the probability of such previously unseen word combinations using available information on ``most similar'' words. #R##N#We describe probabilistic word association models based on distributional word similarity, and apply them to two tasks, language modeling and pseudo-word disambiguation. In the language modeling task, a similarity-based model is used to improve probability estimates for unseen bigrams in a back-off language model. The similarity-based method yields a 20% perplexity improvement in the prediction of unseen bigrams and statistically significant reductions in speech-recognition error. #R##N#We also compare four similarity-based estimation methods against back-off and maximum-likelihood estimation methods on a pseudo-word sense disambiguation task in which we controlled for both unigram and bigram frequency to avoid giving too much weight to easy-to-disambiguate high-frequency configurations. The similarity-based methods perform up to 40% better on this particular task.

Connected through hyperedge HE-1 (induced by source paper "sentence entailment in compositional distributional semantics"):
  with members:
    - "a generalised quantifier theory of natural language in categorical compositional distributional semantics with bialgebras"
    - "the frobenius anatomy of word meanings ii possessive relative pronouns"
    - "coordination in categorical compositional distributional semantics"
    - "graded entailment for compositional distributional semantics"
    - "a frobenius model of information structure in categorical compositional distributional semantics"
    - "open system categorical quantum semantics in natural language processing"
    - "distributional sentence entailment using density matrices"
    - "evaluating neural word representations in tensor based compositional settings"

Connected through hyperedge HE-2 (induced by source paper "frappuccino fault detection through runtime analysis of provenance"):
  with members:
    - "mamadroid detecting android malware by building markov chains of behavioral models"

Connected through hyperedge HE-3 (induced by source paper "distributional inclusion hypothesis for tensor based composition"):
  with members:
    - "sentence entailment in compositional distributional semantics"
    - "graded entailment for compositional distributional semantics"
    - "syntax aware multi sense word embeddings for deep compositional models of meaning"
    - "a study of entanglement in a categorical framework of natural language"
    - "evaluating neural word representations in tensor based compositional settings"
    - "a convolutional neural network for modelling sentences"
    - "experimental support for a categorical compositional distributional model of meaning"
    - "from frequency to meaning vector space models of semantics"

Connected through hyperedge HE-4 (induced by source paper "semantic similarity from natural language and ontology analysis"):
  with members:
    - "description and evaluation of semantic similarity measures approaches"
    - "domain and function a dual space model of semantic relations and compositions"
    - "from frequency to meaning vector space models of semantics"
    - "wikipedia based semantic interpretation for natural language processing"
    - "similarity of semantic relations"
    - "the google similarity distance"
    - "measuring praise and criticism inference of semantic orientation from association"
    - "mining the web for synonyms pmi ir versus lsa on toefl"

Connected through hyperedge HE-5 (induced by source paper "detecting singleton review spammers using semantic similarity"):
  with members:
    - "finding deceptive opinion spam by any stretch of the imagination"

Connected through hyperedge HE-6 (induced by source paper "semantic measures for the comparison of units of language concepts or entities from text and knowledge base analysis"):
  with members:
    - "description and evaluation of semantic similarity measures approaches"
    - "distributional measures as proxies for semantic relatedness"
    - "roget s thesaurus and semantic similarity"
    - "distributional measures of semantic distance a survey"
    - "a new similarity measure for taxonomy based on edge counting"
    - "a semantic relatedness measure based on combined encyclopedic ontological and collocational knowledge"
    - "serimi resource description similarity rdf instance matching and interlinking"
    - "hitting and commute times in large graphs are often misleading"

Connected through hyperedge HE-7 (induced by source paper "semantic sort a supervised approach to personalized semantic relatedness"):
  with members:
    - "roget s thesaurus and semantic similarity"
    - "active learning using smooth relative regret approximations with applications"
    - "a semantic relatedness measure based on combined encyclopedic ontological and collocational knowledge"
    - "text relatedness based on a word thesaurus"
    - "wikipedia based semantic interpretation for natural language processing"
    - "the google similarity distance"
    - "roget s thesaurus as a lexical resource for natural language processing"
    - "thumbs up or thumbs down semantic orientation applied to unsupervised classification of reviews"

Connected through hyperedge HE-8 (induced by source paper "distributional measures of semantic distance a survey"):
  with members:
    - "roget s thesaurus and semantic similarity"
    - "mining the web for synonyms pmi ir versus lsa on toefl"
    - "measures of distributional similarity"
    - "semantic similarity in a taxonomy an information based measure and its application to problems of ambiguity in natural language"

Question: Please tell me which class the center node 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)