2023 - Research.com Computer Science in United Kingdom Leader Award
2022 - Research.com Computer Science in Japan Leader Award
His primary areas of study are Artificial intelligence, Natural language processing, Parsing, Information retrieval and Biomedical text mining. His studies deal with areas such as Machine learning, Task and Pattern recognition as well as Artificial intelligence. His Natural language processing study incorporates themes from Domain and Probabilistic logic.
Jun'ichi Tsujii has included themes like Object, Syntax, Natural language and Component in his Parsing study. His Information retrieval study integrates concerns from other disciplines, such as Text mining, Web application, Annotation and The Internet. His Biomedical text mining research is multidisciplinary, incorporating elements of Event and Distributed computing.
His scientific interests lie mostly in Artificial intelligence, Natural language processing, Parsing, Information retrieval and Task. His Artificial intelligence research incorporates themes from Machine learning, Speech recognition and Biomedical text mining. His Natural language processing study combines topics in areas such as Domain, Annotation and Grammar.
His research integrates issues of Syntax and Rule-based machine translation in his study of Parsing. His work carried out in the field of Information retrieval brings together such families of science as Text mining and Named-entity recognition. In his work, S-attributed grammar and Parsing expression grammar is strongly intertwined with Parser combinator, which is a subfield of Top-down parsing.
Jun'ichi Tsujii mostly deals with Artificial intelligence, Natural language processing, Task, Biomedical text mining and Information retrieval. The study incorporates disciplines such as Named-entity recognition and Data mining in addition to Artificial intelligence. He combines subjects such as Domain, Head-driven phrase structure grammar and Coreference with his study of Natural language processing.
His studies deal with areas such as Annotation and Ontology as well as Task. His research integrates issues of Class, Information extraction, Set, Event and Software in his study of Biomedical text mining. His research on Information retrieval also deals with topics like
The scientist’s investigation covers issues in Artificial intelligence, Natural language processing, Task, Biomedical text mining and Event. His Artificial intelligence research incorporates themes from Named-entity recognition, Data mining and Pattern recognition. His work carried out in the field of Natural language processing brings together such families of science as Class, Joint and Text segmentation.
His biological study spans a wide range of topics, including Domain and Information retrieval. His study in Information retrieval is interdisciplinary in nature, drawing from both Text mining, Web application and Annotation. Jun'ichi Tsujii interconnects Data science, Coreference and Set in the investigation of issues within Biomedical text mining.
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GENIA corpus—a semantically annotated corpus for bio-textmining
Jin-Dong Kim;Tomoko Ohta;Yuka Tateisi;Jun'ichi Tsujii.
brat: a Web-based Tool for NLP-Assisted Text Annotation
Pontus Stenetorp;Sampo Pyysalo;Goran Topić;Tomoko Ohta.
conference of the european chapter of the association for computational linguistics (2012)
Overview of BioNLP'09 Shared Task on Event Extraction
Jin-Dong Kim;Tomoko Ohta;Sampo Pyysalo;Yoshinobu Kano.
north american chapter of the association for computational linguistics (2009)
Developing a robust part-of-speech tagger for biomedical text
Yoshimasa Tsuruoka;Yuka Tateishi;Jin-Dong Kim;Tomoko Ohta.
panhellenic conference on informatics (2005)
Corpus annotation for mining biomedical events from literature
Jin Dong Kim;Tomoko Ohta;Jun'ichi Tsujii;Jun'ichi Tsujii.
BMC Bioinformatics (2008)
Text mining and its potential applications in systems biology
Sophia Ananiadou;Douglas B. Kell;Jun ichi Tsujii;Jun ichi Tsujii.
Trends in Biotechnology (2006)
Accomplishments and challenges in literature data mining for biology
Lynette Hirschman;Jong C. Park;Junichi Tsujii;Limsoon Wong.
Extracting the names of genes and gene products with a hidden Markov model
Nigel Collier;Chikashi Nobata;Jun-ichi Tsujii.
international conference on computational linguistics (2000)
Tuning support vector machines for biomedical named entity recognition
Jun'ichi Kazama;Takaki Makino;Yoshihiro Ohta;Jun'ichi Tsujii.
meeting of the association for computational linguistics (2002)
Bidirectional Inference with the Easiest-First Strategy for Tagging Sequence Data
Yoshimasa Tsuruoka;Jun'ichi Tsujii.
empirical methods in natural language processing (2005)
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