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Cambridge University Press по журналам "Natural Language Engineering"

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  • NEVIAROUSKAYA ALENA; PRENDINGER HELMUT; ISHIZUKA MITSURU (Cambridge University Press. Cambridge, UK, 2011-01-01)
    In this paper, we address the tasks of recognition and interpretation of affect communicated through text messaging in online communication environments. Specifically, we focus on Instant Messaging (IM) or blogs, where ...
  • MacKay David J. C.; Peto Linda C. Bauman (Cambridge University Press. Cambridge, UK, 1995-09-01)
    We discuss a hierarchical probabilistic model whose predictions are similar to those of the popular language modelling procedure known as ‘smoothing’. A number of interesting differences from smoothing emerge. The insights ...
  • MALETTI ANDREAS (Cambridge University Press. Cambridge, UK, 2011-03-01)
    Synchronous tree substitution grammars (stsg) are a (formal) tree transformation model that is used in the area of syntax-based machine translation. A competitor that is at least as expressive as stsg is proposed and ...
  • SOLORIO T.; SHERMAN M.; LIU Y.; BEDORE L. M.; PEÑA E. D.; IGLESIAS A. (Cambridge University Press. Cambridge, UK, 2011-07-01)
    In this work we study how features typically used in natural language processing tasks, together with measures from syntactic complexity, can be adapted to the problem of developing language profiles of bilingual children. ...
  • Pulman Stephen G. (Cambridge University Press. Cambridge, UK, 1995-09-01)
    Artificial languages for person-machine communication seldom display the most characteristic properties of natural languages, such as the use of anaphoric or other referring expressions, or ellipsis. This paper argues that ...
  • CHEW PETER A.; BADER BRETT W.; HELMREICH STEPHEN; ABDELALI AHMED; VERZI STEPHEN J. (Cambridge University Press. Cambridge, UK, 2011-01-01)
    In this article, we demonstrate several novel ways in which insights from information theory (IT) and computational linguistics (CL) can be woven into a vector-space-model (VSM) approach to information retrieval (IR). Our ...
  • VAN DE CRUYS TIM (Cambridge University Press. Cambridge, UK, 2010-10-01)
    The distributional similarity methods have proven to be a valuable tool for the induction of semantic similarity. Until now, most algorithms use two-way co-occurrence data to compute the meaning of words. Co-occurrence ...
  • HÖGBERG JOHANNA (Cambridge University Press. Cambridge, UK, 2011-03-01)
    We present a randomised inference algorithm for regular tree languages. The algorithm takes as input two disjoint finite nonempty sets of trees 𝒫 and 𝒩 and outputs a nondeterministic finite tree automaton that accepts ...
  • Bachenko Joan; Fitzpatrick Eileen; Daugherty Jeffrey (Cambridge University Press. Cambridge, UK, 1995-06-01)
    Text-to-speech systems are currently designed to work on complete sentences and paragraphs, thereby allowing front end processors access to large amounts of linguistic context. Problems with this design arise when applications ...
  • AI HUA; LITMAN DIANE (Cambridge University Press. Cambridge, UK, 2011-10-01)
    While different user simulations are built to assist dialog system development, there is an increasing need to quickly assess the quality of the user simulations reliably. Previous studies have proposed several automatic ...
  • Han Young S.; Choi Key-Sun (Cambridge University Press. Cambridge, UK, 1995-06-01)
    Inside parsing is a best parse parsing method based on the Inside algorithm that is often used in estimating probabilistic parameters of stochastic context free grammars. It gives a best parse in O(N3G3) time where N is ...
  • RECASENS M.; HOVY E. (Cambridge University Press. Cambridge, UK, 2011-10-01)
    This paper addresses the current state of coreference resolution evaluation, in which different measures (notably, MUC, B3, CEAF, and ACE-value) are applied in different studies. None of them is fully adequate, and their ...
  • LI JIANGUO; BREW CHRIS (Cambridge University Press. Cambridge, UK, 2010-10-01)
    Lapata and Brew (Computational Linguistics, vol. 30, 2004, pp. 295–313) (hereafter LB04) obtain from untagged texts a statistical prior model that is able to generate class preferences for ambiguous Lewin (English Verb ...
  • GUO YUQING; WANG HAIFENG; VAN GENABITH JOSEF (Cambridge University Press. Cambridge, UK, 2011-10-01)
    This paper presents a general-purpose, wide-coverage, probabilistic sentence generator based on dependency n-gram models. This is particularly interesting as many semantic or abstract syntactic input specifications for ...
  • NINOMIYA TAKASHI; MATSUZAKI TAKUYA; SHIMIZU NOBUYUKI; NAKAGAWA HIROSHI (Cambridge University Press. Cambridge, UK, 2011-07-01)
    Many parsing techniques assume the use of a packed parse forest to enable efficient and accurate parsing. However, they suffer from an inherent problem that derives from the restriction of locality in the packed parse ...
  • YANG FAN; HEEMAN PETER A.; HOLLINGSHEAD KRISTY; STRAYER SUSAN E. (Cambridge University Press. Cambridge, UK, 2008-01-01)
    This paper describes DialogueView, a tool for annotating dialogues with utterance boundaries, speech repairs, speech act tags, and hierarchical discourse blocks. The tool provides three views of a dialogue: WordView, which ...
  • KOTLERMAN LILI; DAGAN IDO; SZPEKTOR IDAN; ZHITOMIRSKY-GEFFET MAAYAN (Cambridge University Press. Cambridge, UK, 2010-10-01)
    Distributional word similarity is most commonly perceived as a symmetric relation. Yet, directional relations are abundant in lexical semantics and in many Natural Language Processing (NLP) settings that require lexical ...
  • BASILI R.; PENNACCHIOTTI M. (Cambridge University Press. Cambridge, UK, 2010-10-01)
    The distributional hypothesis states that words with similar distributional properties have similar semantic properties (Harris 1968). This perspective on word semantics, was early discussed in linguistics (Firth 1957; ...
  • Неизвестный автор (Cambridge University Press. Cambridge, UK, 1995-03-01)
  • Mitkov Ruslan (Cambridge University Press. Cambridge, UK, 2008-01-01)
    I am honoured to address you as the new Executive Editor of the journal, a role I took on recently from Professor John Tait. As someone who, along with the other editors and members of the Editorial Board, has the ...