Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1038/s41467-018-05314-1 |
Predicting natural language descriptions of mono-molecular odorants | |
Gutierrez, E. Dario1; Dhurandhar, Amit2; Keller, Andreas3; Meyer, Pablo1,4; Cecchi, Guillermo A.1 | |
2018-11-26 | |
发表期刊 | NATURE COMMUNICATIONS |
ISSN | 2041-1723 |
出版年 | 2018 |
卷号 | 9 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | There has been recent progress in predicting whether common verbal descriptors such as "fishy", "floral" or "fruity" apply to the smell of odorous molecules. However, accurate predictions have been achieved only for a small number of descriptors. Here, we show that applying natural-language semantic representations on a small set of general olfactory perceptual descriptors allows for the accurate inference of perceptual ratings for monomolecular odorants over a large and potentially arbitrary set of descriptors. This is noteworthy given that the prevailing view is that humans' capacity to identify or characterize odors by name is poor. We successfully apply our semantics-based approach to predict perceptual ratings with an accuracy higher than 0.5 for up to 70 olfactory perceptual descriptors, a ten-fold increase in the number of descriptors from previous attempts. These results imply that the semantic distance between descriptors defines the equivalent of an odorwheel. |
领域 | 资源环境 |
收录类别 | SCI-E ; SSCI |
WOS记录号 | WOS:000451176100004 |
WOS关键词 | OLFACTORY DEFICITS ; ODORS ; ACQUISITION ; PERCEPTION ; COHERENCE |
WOS类目 | Multidisciplinary Sciences |
WOS研究方向 | Science & Technology - Other Topics |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/203888 |
专题 | 资源环境科学 |
作者单位 | 1.TJ Watson IBM Res Lab, Computat Biol Ctr, 1101 Kitchawan Rd, Yorktown Hts, NY 10598 USA; 2.TJ Watson IBM Res Lab, Artificial Intelligence Fdn, 1101 Kitchawan Rd, Yorktown Hts, NY 10598 USA; 3.AK Consulting, 508 East 78th St,Apt 5N, New York, NY 10075 USA; 4.Icahn Sch Med Mt Sinai, Dept Genet & Genom Sci, New York, NY 10029 USA |
推荐引用方式 GB/T 7714 | Gutierrez, E. Dario,Dhurandhar, Amit,Keller, Andreas,et al. Predicting natural language descriptions of mono-molecular odorants[J]. NATURE COMMUNICATIONS,2018,9. |
APA | Gutierrez, E. Dario,Dhurandhar, Amit,Keller, Andreas,Meyer, Pablo,&Cecchi, Guillermo A..(2018).Predicting natural language descriptions of mono-molecular odorants.NATURE COMMUNICATIONS,9. |
MLA | Gutierrez, E. Dario,et al."Predicting natural language descriptions of mono-molecular odorants".NATURE COMMUNICATIONS 9(2018). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论