Results 11 to 20 of about 192,314 (323)
Modelling function words improves unsupervised word segmentation [PDF]
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2014 Inspired by experimental psychological findings suggesting that function words play a special role in word learning, we make a simple modification to an Adaptor Grammar based Bayesian word segmentation model to allow it to learn sequences of monosyllabic “function words” at the beginnings and endings of collocations of (possibly multi-syllabic) words ...
Mark Johnson +3 more
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Nonparametric Bayesian Semi-supervised Word Segmentation [PDF]
Transactions of the Association for Computational Linguistics, 2021 This paper presents a novel hybrid generative/discriminative model of word segmentation based on nonparametric Bayesian methods. Unlike ordinary discriminative word segmentation which relies only on labeled data, our semi-supervised model also leverages a huge amounts of unlabeled text to automatically learn new “words”, and further constrains them by
Ryo Fujii, Ryo Domoto, Daichi Mochihashi
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Semantic Segmentation Method of Tibetan Sentences [PDF]
Jisuanji gongcheng, 2020 Sentences are characters or words that are combined according to grammatical rules.Semantic segmentation is a decoding problem of sentence combination rules,that is,parsing the meaning of sentences.If the semantic analysis is performed directly after the
ROU Te, SE Chajia, CAI Rangjia
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CWSXLNet: A Sentiment Analysis Model Based on Chinese Word Segmentation Information Enhancement
Applied Sciences, 2023 This paper proposed a method for improving the XLNet model to address the shortcomings of segmentation algorithm for processing Chinese language, such as long sub-word lengths, long word lists and incomplete word list coverage.
Shiqian Guo +4 more
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Do Chinese readers follow the national standard rules for word segmentation during reading? [PDF]
PLoS ONE, 2013 We conducted a preliminary study to examine whether Chinese readers' spontaneous word segmentation processing is consistent with the national standard rules of word segmentation based on the Contemporary Chinese language word segmentation specification ...
Ping-Ping Liu +3 more
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Detect ‘protein word’ based on unsupervised word segmentation
, 2015 Unsupervised word segmentation methods were applied to analyze the protein sequence. Protein sequences, such as ‘MTMDKSELVQKA …..’, were used as input to these methods. Segmented ‘protein word’ sequences, such as ‘MTM DKSE LVQKA’, were then obtained.
Liang Wang, Kaiyong Zhao
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Detecting “protein words” through unsupervised word segmentation [PDF]
F1000Research, 2015 Unsupervised word segmentation methods were applied to analyze protein sequences. Protein sequences, such as “MTMDKSELVQKA…,” were used as input to these methods. Segmented protein word sequences, such as “MTM DKSE LVQKA,” were then obtained.
Liang, Wang, KaiYong, Zhao
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An Algorithm Rapidly Segmenting Chinese Sentences into Individual Words [PDF]
MATEC Web of Conferences, 2019 This paper proposes an improved Trie tree structure. The tree node records the position information of the characters participating in the word formation, and the child node uses the hash search mechanism.
Xiong Zhibin
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Universal Word Segmentation: Implementation and Interpretation [PDF]
Transactions of the Association for Computational Linguistics, 2021 Word segmentation is a low-level NLP task that is non-trivial for a considerable number of languages. In this paper, we present a sequence tagging framework and apply it to word segmentation for a wide range of languages with different writing systems and typological characteristics.
Yan Shao +2 more
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Reduplication facilitates early word segmentation [PDF]
Journal of Child Language, 2017 AbstractThis study explores the possibility that early word segmentation is aided by infants’ tendency to segment words with repeated syllables (‘reduplication’). Twenty-four nine-month-olds were familiarized with passages containing one novel reduplicated word and one novel non-reduplicated word.
Skarabela, Barbora, Ota, Mitsuhiko
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