O
Olga Kononova
Researcher at University of California, Berkeley
Publications - 44
Citations - 1886
Olga Kononova is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Computer science & Information extraction. The author has an hindex of 15, co-authored 35 publications receiving 1011 citations. Previous affiliations of Olga Kononova include University of Massachusetts Lowell & Lawrence Berkeley National Laboratory.
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Unsupervised word embeddings capture latent knowledge from materials science literature
Vahe Tshitoyan,Vahe Tshitoyan,John Dagdelen,John Dagdelen,Leigh Weston,Alexander Dunn,Alexander Dunn,Ziqin Rong,Olga Kononova,Kristin A. Persson,Kristin A. Persson,Gerbrand Ceder,Gerbrand Ceder,Anubhav Jain +13 more
TL;DR: It is shown that materials science knowledge present in the published literature can be efficiently encoded as information-dense word embeddings11–13 (vector representations of words) without human labelling or supervision, suggesting that latent knowledge regarding future discoveries is to a large extent embedded in past publications.
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High Active Material Loading in All‐Solid‐State Battery Electrode via Particle Size Optimization
Tan Shi,Qingsong Tu,Yaosen Tian,Yihan Xiao,Yihan Xiao,Lincoln J. Miara,Olga Kononova,Gerbrand Ceder,Gerbrand Ceder +8 more
TL;DR: Shi et al. as mentioned in this paper demonstrated with both modeling and experiments that in the regime of high cathode loading, the utilization of cathode material in the solid-state composite is highly dependent on the particle size ratio of the cathode to the solid state conductor.
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Text-mined dataset of inorganic materials synthesis recipes.
Olga Kononova,Haoyan Huo,Haoyan Huo,Tanjin He,Tanjin He,Ziqin Rong,Tiago Botari,Tiago Botari,Wenhao Sun,Vahe Tshitoyan,Vahe Tshitoyan,Gerbrand Ceder,Gerbrand Ceder +12 more
TL;DR: A dataset of “codified recipes” for solid-state synthesis automatically extracted from scientific publications is generated by using text mining and natural language processing approaches for predicting inorganic materials synthesis.
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Named Entity Recognition and Normalization Applied to Large-Scale Information Extraction from the Materials Science Literature.
Leigh Weston,Vahe Tshitoyan,John Dagdelen,Olga Kononova,Amalie Trewartha,Kristin A. Persson,Gerbrand Ceder,Anubhav Jain +7 more
TL;DR: It is demonstrated that simple database queries can be used to answer complex ``meta-questions" of the published literature that would have previously required laborious, manual literature searches to answer.
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Data-driven materials research enabled by natural language processing and information extraction
Elsa Olivetti,Jacqueline M. Cole,Jacqueline M. Cole,Edward Kim,Olga Kononova,Olga Kononova,Gerbrand Ceder,Gerbrand Ceder,Thomas Yong-Jin Han,Anna M. Hiszpanski +9 more
TL;DR: This review focuses on the progress and practices of natural language processing and text mining of materials science literature and highlights opportunities for extracting additional information beyond text contained in figures and tables in articles.