His primary scientific interests are in Artificial intelligence, Natural language processing, Thin film, Machine learning and Analytical chemistry. His Artificial intelligence study frequently draws connections between adjacent fields such as Pattern recognition. His Natural language processing study combines topics from a wide range of disciplines, such as Annotation, Context, Speech recognition and Word.
His Thin film research incorporates elements of Optoelectronics, Doping, Molecular beam epitaxy, Epitaxy and Substrate. Yuji Matsumoto has researched Machine learning in several fields, including Data mining and Identification. His Analytical chemistry study incorporates themes from Magnetic semiconductor, Rutile and Exciton.
His scientific interests lie mostly in Artificial intelligence, Natural language processing, Thin film, Analytical chemistry and Epitaxy. The Artificial intelligence study combines topics in areas such as Speech recognition and Pattern recognition. His study in Natural language processing is interdisciplinary in nature, drawing from both Dependency and Annotation.
His Thin film research includes themes of Optoelectronics, Substrate, Chemical engineering and Molecular beam epitaxy. Yuji Matsumoto combines topics linked to Electron diffraction with his work on Analytical chemistry. In most of his Epitaxy studies, his work intersects topics such as Crystallography.
The scientist’s investigation covers issues in Artificial intelligence, Natural language processing, Ionic liquid, Chemical engineering and Thin film. Artificial intelligence and Pattern recognition are frequently intertwined in his study. His research integrates issues of Tree and Annotation in his study of Natural language processing.
His Ionic liquid research includes elements of Chemical vapor deposition, Pentacene, Contact angle, Layer and Electrochemistry. In his research on the topic of Thin film, Ellipsometry is strongly related with Analytical chemistry. Yuji Matsumoto combines subjects such as Optoelectronics and Epitaxy with his study of Pulsed laser deposition.
His primary areas of study are Artificial intelligence, Natural language processing, Sentence, Dependency and Parsing. The various areas that Yuji Matsumoto examines in his Artificial intelligence study include Machine learning and Pattern recognition. Many of his studies on Natural language processing involve topics that are commonly interrelated, such as Tree.
His study explores the link between Tree and topics such as Construct that cross with problems in Dependency grammar. The Sentence study combines topics in areas such as Image processing, Interpretability, Theoretical computer science and Word embedding. Yuji Matsumoto interconnects Graph and Identification in the investigation of issues within Parsing.
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Room-Temperature Ferromagnetism in Transparent Transition Metal-Doped Titanium Dioxide
Yuji Matsumoto;Makoto Murakami;Tomoji Shono;Tetsuya Hasegawa.
Applying Conditional Random Fields to Japanese Morphological Analysis
Taku Kudo;Kaoru Yamamoto;Yuji Matsumoto.
empirical methods in natural language processing (2004)
Statistical Dependency Analysis with Support Vector Machines
Hiroyasu Yamada;Yuji Matsumoto.
international workshop/conference on parsing technologies (2003)
High throughput fabrication of transition-metal-doped epitaxial ZnO thin films: A series of oxide-diluted magnetic semiconductors and their properties
Zhengwu Jin;Tomoteru Fukumura;M. Kawasaki;K. Ando.
Applied Physics Letters (2001)
Chunking with support vector machines
Taku Kudo;Yuji Matsumoto.
north american chapter of the association for computational linguistics (2001)
Japanese dependency analysis using cascaded chunking
Taku Kudo;Yuji Matsumoto.
international conference on computational linguistics (2002)
Use of support vector learning for chunk identification
Taku Kudoh;Yuji Matsumoto.
conference on computational natural language learning (2000)
Magneto-optical properties of ZnO-based diluted magnetic semiconductors
K. Ando;H. Saito;Zhengwu Jin;T. Fukumura.
Journal of Applied Physics (2001)
Collecting evaluative expressions for opinion extraction
Nozomi Kobayashi;Kentaro Inui;Yuji Matsumoto;Kenji Tateishi.
international joint conference on natural language processing (2004)
Room-temperature stimulated emission of excitons in ZnO/(Mg, Zn)O superlattices
A. Ohtomo;K. Tamura;M. Kawasaki;T. Makino.
Applied Physics Letters (2000)
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