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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 21 – 38 of 38 21 Translate and label! An encoder-decoder approach for cross-lingual semantic role labeling Daza, Angel [Verfasser]; Frank, Anette [Verfasser]; Inui, Kentaro [Herausgeber]. - Mannheim : Leibniz-Institut für Deutsche Sprache (IDS), Bibliothek, 2019 DNB Subject Category Language Show details 22 Cross-lingual semantic specialization via lexical relation induction Glavaš, Goran; Vulić, Ivan; Korhonen, Anna. - : Association for Computational Linguistics, 2019 BASE Show details 23 Do we really need fully unsupervised cross-lingual embeddings? Vulić, Ivan; Glavaš, Goran; Reichart, Roi. - : Association for Computational Linguistics, 2019 BASE Show details 24 Pointwise HSIC: A Linear-Time Kernelized Co-occurrence Norm for Sparse Linguistic Expressions ... Yokoi, Sho; Kobayashi, Sosuke; Fukumizu, Kenji. - : arXiv, 2018 BASE Show details 25 Unsupervised Learning of Style-sensitive Word Vectors ... Akama, Reina; Watanabe, Kento; Yokoi, Sho. - : arXiv, 2018 BASE Show details 26 The mechanism of additive composition [<Journal>] Tian, Ran [Verfasser]; Okazaki, Naoaki [Sonstige]; Inui, Kentaro [Sonstige] DNB Subject Category Language Show details 27 Other Topics You May Also Agree or Disagree: Modeling Inter-Topic Preferences using Tweets and Matrix Factorization ... Sasaki, Akira; Hanawa, Kazuaki; Okazaki, Naoaki. - : arXiv, 2017 BASE Show details 28 An Attentive Neural Architecture for Fine-grained Entity Type Classification ... Shimaoka, Sonse; Stenetorp, Pontus; Inui, Kentaro. - : arXiv, 2016 BASE Show details 29 Advances in probabilistic and other parsing technologies Hahn, Udo (Mitarb.); Sornlertlamvanich, Virach (Mitarb.); Vijay-Shanker, K. (Mitarb.). - Dordrecht [u.a.] : Kluwer, 2000 BLLDB UB Frankfurt Linguistik Show details 30 Integration of speech and image understanding : proceedings ; 21 September 1999, Corfu, Greece Roy, Deb K. (Mitarb.); Inui, Kentaro (Mitarb.); Denzler, J. (Mitarb.). - Los Alamitos, Calif. [u.a.] : IEEE Computer Society, 1999 BLLDB UB Frankfurt Linguistik Show details 31 Articles - Selective Sampling for Example-based Word Sense Disambiguation Fujii, Atsushi; Inui, Kentaro; Tokunaga, Takenobu... In: Computational linguistics. - Cambridge, Mass. : MIT Press 24 (1998) 4, 573-598 OLC Linguistik Show details 32 Selective sampling for example-based word sense disambiguation Fujii, Atsushi; Inui, Kentaro; Tokunaga, Takenobu... In: Computational linguistics. - Cambridge, Mass. : MIT Press 24 (1998) 4, 573-597 BLLDB Show details 33 A New Probabilistic LR Language Model for Statistical Parsing Inui Kentaro; Virach Sornlertlamvanich; Tanaka Hozumi; Ta; Tokunaga Takenobu In: ftp://ftp.cs.titech.ac.jp/lab/tanaka/papers/97/inui97a.ps.gz (1997) Abstract: This paper presents a newly formalized probabilistic LR language model. Our model inherits its essential features from Briscoe and Carroll's generalized probabilistic LR (PLR) model [3], which obtains context-sensitivity by assigning a probability to each LR parsing action according to its left and right context. However, our model is simpler while maintaining a higher degree of context-sensitivity as compared to Briscoe and Carroll's model. In this paper, we first formalize our PLR model and enumerate some of its features. We then discuss the differences between Briscoe and Carroll's model and ours. We also qualitatively compare a model based on canonical LR with one based on lookahead LR. 1 Introduction The increasing availability of text corpora has been encouraging researchers to explore statistical approaches for various tasks in natural language processing. Statistical parsing is one of these approaches. In statistical parsing, one of the most straightforward methodologies is to. URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.54.4148 BASE Hide details 34 Natural Language Analysis and Generation Technologies Tanaka Hozumi; Takenobu Tokunaga; K. G. Suresh... In: ftp://ftp.cs.titech.ac.jp/pub/TR/93/TR93-0028.ps.gz (1993) BASE Show details 35 Text Revision: A Model and Its Implementation Inui Kentaro; Takenobu Tokunaga; Tanaka Hozumi In: ftp://ftp.cs.titech.ac.jp/pub/TR/92/TR92-0011.ps.gz (1992) BASE Show details 36 An Empirical Study on Statistical Disambiguation of Japanese Dependency Structures Using a Lexically Sensitive Language Model Shirai Kiyoaki; Inui Kentaro; Tanaka Hozumi... In: http://galaga.jaist.ac.jp:8000/~kshirai/papers/shirai97d.pdf BASE Show details 37 An Empirical Evaluation on Statistical Parsing of Japanese Sentences using Lexical Association Statistics Shirai Kiyoaki; Inui Kentaro; Tokunaga Takenobu... In: http://www.aclweb.org/anthology-new/W/W98/W98-1510.pdf BASE Show details 38 Fine-grained Utterance Delimitation and Organization in Incremental Explanation Generation Inui Kentaro; Sakaniwa Katsuyuki; Ishizawa Hiroaki... In: ftp://ftp.cs.titech.ac.jp/lab/tanaka/papers/97/inui97d.ps.gz BASE Show details Page: 1 2

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