{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T18:23:10Z","timestamp":1778782990024,"version":"3.51.4"},"reference-count":1,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T00:00:00Z","timestamp":1674432000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T00:00:00Z","timestamp":1674432000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Scientometrics"],"published-print":{"date-parts":[[2023,3]]},"DOI":"10.1007\/s11192-022-04628-8","type":"journal-article","created":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T05:02:31Z","timestamp":1674450151000},"page":"1465-1472","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Machine learning and artificial intelligence for science, technology, innovation mapping and forecasting: Review, synthesis, and applications"],"prefix":"10.1007","volume":"128","author":[{"given":"Daniel","family":"Hain","sequence":"first","affiliation":[]},{"given":"Roman","family":"Jurowetzki","sequence":"additional","affiliation":[]},{"given":"Sungjoo","family":"Lee","sequence":"additional","affiliation":[]},{"given":"Yuan","family":"Zhou","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,1,23]]},"reference":[{"key":"4628_CR1","doi-asserted-by":"crossref","unstructured":"Grover, A., and Leskovec, J. (2016). node2vec: Scalable feature learning for networks. In Proceedings of the 22nd ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 855-864).","DOI":"10.1145\/2939672.2939754"}],"container-title":["Scientometrics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11192-022-04628-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11192-022-04628-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11192-022-04628-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,4]],"date-time":"2023-03-04T08:18:37Z","timestamp":1677917917000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11192-022-04628-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,23]]},"references-count":1,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2023,3]]}},"alternative-id":["4628"],"URL":"https:\/\/doi.org\/10.1007\/s11192-022-04628-8","relation":{},"ISSN":["0138-9130","1588-2861"],"issn-type":[{"value":"0138-9130","type":"print"},{"value":"1588-2861","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,23]]},"assertion":[{"value":"22 December 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 December 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 January 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}