鶴岡慶雅 研究者
鶴岡, 慶雅, 1974-
쓰루오카 요시마사 1974-
鶴岡, 慶雅
VIAF ID: 16150516744503442536 (Personal)
Permalink: http://viaf.org/viaf/16150516744503442536
Preferred Forms
-
100 1 _
‡a
鶴岡, 慶雅
-
100 1 _
‡a
鶴岡, 慶雅,
‡d
1974-
-
100 0 _
‡a
鶴岡慶雅
‡c
研究者
-
100 1 _
‡a
쓰루오카 요시마사
‡d
1974-
4xx's: Alternate Name Forms (12)
Works
| Title | Sources |
|---|---|
| Accelerating the annotation of sparse named entities by dynamic sentence selection |
|
| AGRA: analysis of gene ranking algorithms. |
|
| Automatic recognition of topic-classified relations between prostate cancer and genes using MEDLINE abstracts. |
|
| Bidirectional inference with the easiest-first strategy for tagging sequence data |
|
| [Deep Learning and Natural Language Processing] |
|
| Developing a Robust Part-of-Speech Tagger for Biomedical Text |
|
| Discovering and visualizing indirect associations between biomedical concepts. |
|
| FACTA: a text search engine for finding associated biomedical concepts |
|
| Filling the gaps between tools and users: a tool comparator, using protein-protein interaction as an example. |
|
| How to make the most of NE dictionaries in statistical NER. |
|
| Identifying synonymy between relational phrases using word embeddings |
|
| Improving the performance of dictionary-based approaches in protein name recognition. |
|
| Indexing anatomical concepts to OMIM Clinical Synopsis using the UMLS Metathesaurus |
|
| Integration of metabolic databases for the reconstruction of genome-scale metabolic networks |
|
| Introduction to the bio-entity recognition task at JNLPBA |
|
| Kobun kaiseki. |
|
| Learning Robust Options by Conditional Value at Risk Optimization |
|
| Learning string similarity measures for gene/protein name dictionary look-up using logistic regression |
|
| No to eai : Gengo to shiko eno apurochi. |
|
| Normalizing biomedical terms by minimizing ambiguity and variability |
|
| PathText: a text mining integrator for biological pathway visualizations |
|
| Probabilistic Chinese word segmentation with non-local information and stochastic training |
|
| Semantic retrieval for the accurate identification of relational concepts in massive textbases |
|
| Wide-coverage relation extraction from MEDLINE using deep syntax. |
|
| 뇌와 AI |
|
| 脳とAI : 言語と思考へのアプローチ |
|
| 構文解析 = Syntactic Analysis |
|
