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Improved prediction of transcription binding sites from chromatin modification data
In this paper we apply machine learning to the task of predicting transcription factor binding sites by combining information on …
Kengo Sato, Tom Whitington, Timothy L. Bailey, Paul Horton
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Stem Kernels for RNA Sequence Analyses
Several computational methods based on stochastic context-free grammars have been developed for modeling and analyzing functional RNA …
Yasubumi Sakakibara, Kiyoshi Asai, Kengo Sato
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Preferential Presentation of Japanese Near-synonyms using Definition Statements
This paper proposes a new method of ranking near-synonyms ordered by their suitability of nuances in a particular context. Our method …
Hiroyuki Okamoto, Kengo Sato, Hiroaki Saito
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Extracting Word Sequence Correspondences with Support Vector Machines
This paper proposes a learning and extracting method of word sequence correspondences from non-aligned parallel corpora with Support …
Kengo Sato, Hiroaki Saito
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Maximum Entropy Model Learning of the Translation Rules
Kengo Sato, Masakazu Nakanishi
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Segmenting Sentences into Linky Strings Using D-bigram Statistics
It is obvious that segmentation takes an important role in natural language processing(NLP), especially for the languages whose …
Shiho Nobesawa, Junya Tsutsumi, Sun Da Jiang, Tomohisa Sano, Kengo Sato, Masakazu Nakanishi
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