{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,20]],"date-time":"2025-03-20T04:10:24Z","timestamp":1742443824588,"version":"3.40.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685724","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,3,17]],"date-time":"2025-03-17T00:00:00Z","timestamp":1742169600000},"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":[[2025,3,17]]},"abstract":"<jats:p>In this paper, we proposed an implementation method of a system according to \u2018tri-knowledge base with personal context vectors model\u2019 that proposed in previous study. The system aims not only a single set of contexts and knowledge base, but also create snapshot and stored it as the memories of the changes in timeseries. Organisational contexts vectors were added to the system. As well as the personal context vectors to absorb personal preferences, the organisational context vectors can absorb organisational preference without changing the knowledgebase. Experiments were conducted to verify the functionality of memorising the changes in timeseries and the effects of the organisational context vector.<\/jats:p>","DOI":"10.3233\/faia241582","type":"book-chapter","created":{"date-parts":[[2025,3,19]],"date-time":"2025-03-19T08:29:09Z","timestamp":1742372949000},"source":"Crossref","is-referenced-by-count":0,"title":["\u2018Anywhere to Work\u2019. An Implementation Method for Selecting Workplaces According to the Contexts of Workplace"],"prefix":"10.3233","author":[{"given":"Hitoshi","family":"Kumagai","sequence":"first","affiliation":[{"name":"Graduate School of Data Science, Musashino University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Naoki","family":"Ishibashi","sequence":"additional","affiliation":[{"name":"Graduate School of Data Science, Musashino University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yasushi","family":"Kiyoki","sequence":"additional","affiliation":[{"name":"Graduate School of Data Science, Musashino University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Information Modelling and Knowledge Bases XXXVI"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA241582","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,19]],"date-time":"2025-03-19T08:29:09Z","timestamp":1742372949000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA241582"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,17]]},"ISBN":["9781643685724"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia241582","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3,17]]}}}