{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,12,2]],"date-time":"2023-12-02T00:50:38Z","timestamp":1701478238637},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684444","type":"print"},{"value":"9781643684451","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T00:00:00Z","timestamp":1701302400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,11,30]]},"abstract":"<jats:p>This paper studies a talent comprehensive quality platform based on big data analysis, including: unified data collection layer, which gathers talent data from various data sources to HDFS storage in an adaptive way; At the basic data platform layer, the talent data from the unified data collection layer is analyzed with big data to form a talent comprehensive quality evaluation report, which provides publishing and query; The application display layer displays the talent comprehensive quality evaluation report published or queried by the basic data platform layer. This paper realizes the comprehensive quality evaluation and management of talents, with high accuracy, convenience and security. In addition, this paper proposes a multimodal information fusion method, including image, text, and audio data, to comprehensively describe and predict the characteristics of talents. The experimental results show that the user portrait modeling method based on multi-modal information in this paper has achieved better performance in the talent feature prediction task.<\/jats:p>","DOI":"10.3233\/faia230924","type":"book-chapter","created":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T15:58:52Z","timestamp":1701446332000},"source":"Crossref","is-referenced-by-count":0,"title":["Key Technologies of Talent Portrait Based on Big Data Analysis"],"prefix":"10.3233","author":[{"given":"Yang","family":"Zhang","sequence":"first","affiliation":[{"name":"Beijing Fibrlink Communcations Co., Ltd,State Grid Information & Telecommunction Co., Ltd, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiao","family":"Sun","sequence":"additional","affiliation":[{"name":"Beijing Fibrlink Communcations Co., Ltd,State Grid Information & Telecommunction Co., Ltd, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changyu","family":"Du","sequence":"additional","affiliation":[{"name":"Beijing Fibrlink Communcations Co., Ltd,State Grid Information & Telecommunction Co., Ltd, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Ji","sequence":"additional","affiliation":[{"name":"Beijing Fibrlink Communcations Co., Ltd,State Grid Information & Telecommunction Co., Ltd, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dan","family":"Liu","sequence":"additional","affiliation":[{"name":"Beijing Fibrlink Communcations Co., Ltd,State Grid Information & Telecommunction Co., Ltd, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Zhao","sequence":"additional","affiliation":[{"name":"Beijing Fibrlink Communcations Co., Ltd,State Grid Information & Telecommunction Co., Ltd, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Advances in Artificial Intelligence, Big Data and Algorithms"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA230924","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T15:58:58Z","timestamp":1701446338000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA230924"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,30]]},"ISBN":["9781643684444","9781643684451"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia230924","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,30]]}}}