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    JMLR
    2012
    220views Programming Languages» more  JMLR 2012»
    Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing
    12 years 12 months ago
    Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing
    Download  jmlr.csail.mit.edu
    Open-text semantic parsers are designed to interpret any statement in natural language by inferring a corresponding meaning representation (MR – a formal representation of its s...
    Antoine Bordes, Xavier Glorot, Jason Weston, Yoshu...
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    NIPS
    2003
    116views Information Technology» more  NIPS 2003»
    Unsupervised Context Sensitive Language Acquisition from a Large Corpus
    14 years 10 months ago
    Unsupervised Context Sensitive Language Acquisition from a Large Corpus
    Download  kybele.psych.cornell.edu
    We describe a pattern acquisition algorithm that learns, in an unsupervised fashion, a streamlined representation of linguistic structures from a plain natural-language corpus. Th...
    Zach Solan, David Horn, Eytan Ruppin, Shimon Edelm...
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    LREC
    2010
    225views Education» more  LREC 2010»
    The Architecture of FunGramKB
    14 years 11 months ago
    The Architecture of FunGramKB
    Download  www.fungramkb.com
    Natural language understanding systems require a knowledge base provided with conceptual representations reflecting the structure of human beings' cognitive system. Although ...
    Carlos Periñán-Pascual, Francisco Ar...
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    EMNLP
    2009
    115views Natural Language Processing» more  EMNLP 2009»
    Statistical Estimation of Word Acquisition with Application to Readability Prediction
    14 years 7 months ago
    Statistical Estimation of Word Acquisition with Application to Readability Prediction
    Download  research.microsoft.com
    Models of language learning play a central role in a wide range of applications: from psycholinguistic theories of how people acquire new word knowledge, to information systems th...
    Paul Kidwell, Guy Lebanon, Kevyn Collins-Thompson
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    ROMAN
    2007
    IEEE
    179views Robotics» more  ROMAN 2007»
    A Bayesian Network Framework for Vision Based Semantic Scene Understanding
    15 years 3 months ago
    A Bayesian Network Framework for Vision Based Semantic Scene Understanding
    Download  sclab.yonsei.ac.kr
    — For a robot to understand a scene, we have to infer and extract meaningful information from vision sensor data. Since scene understanding consists in recognizing several visual...
    Seung-Bin Im, Keum-Sung Hwang, Sung-Bae Clio
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