{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T23:59:27Z","timestamp":1740182367878,"version":"3.37.3"},"reference-count":58,"publisher":"IOP Publishing","issue":"2","license":[{"start":{"date-parts":[[2022,4,21]],"date-time":"2022-04-21T00:00:00Z","timestamp":1650499200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,4,21]],"date-time":"2022-04-21T00:00:00Z","timestamp":1650499200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100020959","name":"JST-Mirai Program","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100020959","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Mach. Learn.: Sci. 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Potential research topics are selected by analyzing the difference between two research concept networks constructed from research information in articles: one that represents the promise of research topics and is constructed from word embeddings, and one that represents known facts and past research activities and is constructed from statistical information on the appearance patterns of research concepts. The ARTS system is also equipped with functions to search and visualize information about selected research topics to assist in the final determination of a research topic by a scientist. We developed the ARTS system using approximately 100\u200900 articles published in the Computational Materials Science journal. The results of our evaluation demonstrated that research topics studied after 2016 could be generated autonomously from an analysis of the articles published before 2015. This suggests that potential research topics can be effectively selected by using the ARTS system.<\/jats:p>","DOI":"10.1088\/2632-2153\/ac61eb","type":"journal-article","created":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T22:11:50Z","timestamp":1648591910000},"page":"025005","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["ARTS: autonomous research topic selection system using word embeddings and network analysis"],"prefix":"10.1088","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7601-6987","authenticated-orcid":true,"given":"Eri","family":"Teruya","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tadashi","family":"Takeuchi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hidekazu","family":"Morita","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Takayuki","family":"Hayashi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3285-9093","authenticated-orcid":false,"given":"Kanta","family":"Ono","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"266","published-online":{"date-parts":[[2022,4,21]]},"reference":[{"key":"mlstac61ebbib1","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1038\/s41586-020-2442-2","article-title":"A mobile robotic chemist","volume":"583","author":"Burger","year":"2020","journal-title":"Nature"},{"key":"mlstac61ebbib2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41524-017-0056-5","article-title":"Machine learning in materials informatics: recent applications and prospects","volume":"3","author":"Ramprasad","year":"2017","journal-title":"npj Comput. 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