{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,4]],"date-time":"2025-10-04T18:31:12Z","timestamp":1759602672328,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":18,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819785971"},{"type":"electronic","value":"9789819785988"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-981-97-8598-8_17","type":"book-chapter","created":{"date-parts":[[2025,1,16]],"date-time":"2025-01-16T08:07:05Z","timestamp":1737014825000},"page":"191-201","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Method for\u00a0Identifying Business Goals for\u00a0Generative Artificial Intelligence Applications Based on\u00a0Knowledge Distribution Models and\u00a0GQM+Strategies"],"prefix":"10.1007","author":[{"given":"Hironori","family":"Takeuchi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ralf-Christian","family":"H\u00e4rting","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuichiro","family":"Yamamoto","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,17]]},"reference":[{"key":"17_CR1","doi-asserted-by":"crossref","unstructured":"Aldea, A., Iacob, M.E., van Hillegersberg, J., Quartel, D., Bodenstaff, L., Franken, H.: Modeling strategy with archimate. In: Proceedings of the 30th Annual ACM Symposium on Applied Computing, pp. 1211\u20131218 (2015)","DOI":"10.1145\/2695664.2699489"},{"key":"17_CR2","doi-asserted-by":"crossref","unstructured":"Amershi, S., Begel, A., Bird, C., Deliner, R., Gall, H., Kamar, E., Nushi, N.N.B., Zimmermann, T.: Software engineering for machine learning: a case study. In: Proceedings of the 41st International Conference on Software Engineering, pp. 291\u2013300 (2019)","DOI":"10.1109\/ICSE-SEIP.2019.00042"},{"issue":"3\u20134","key":"17_CR3","doi-asserted-by":"publisher","first-page":"245","DOI":"10.3233\/AO-170189","volume":"12","author":"K Baclawski","year":"2017","unstructured":"Baclawski, K., Chan, E.S., Gawlick, D., Liu, Z.H., Ghoneimy, A., Gross, K., Zhang, X.: Framework for ontology-driven decision making. Appl. Ontol. 12(3\u20134), 245\u2013273 (2017)","journal-title":"Appl. Ontol."},{"key":"17_CR4","doi-asserted-by":"crossref","unstructured":"Basili, V., Trendowicz, A., Kowalczyk, M., Heidrich, J., Seaman, C., M\u00fcnch, J., Rombach, D.: Aligning Organizations Through Measurement: The GQM+Strategies Approach. Springer International Publishing (2014)","DOI":"10.1007\/978-3-319-05047-8"},{"key":"17_CR5","doi-asserted-by":"crossref","unstructured":"Beltempo, L., Zerrer, J., H\u00e4rting, R.C., Hoppe, N.: Barriers of Artificial Intelligence in the Health Sector, pp. 251\u2013273 (2022)","DOI":"10.1007\/978-3-031-11170-9_10"},{"key":"17_CR6","doi-asserted-by":"publisher","first-page":"781","DOI":"10.1007\/s10270-023-01105-5","volume":"22","author":"J C\u00e1mara","year":"2023","unstructured":"C\u00e1mara, J., Troya, J., Burgue\u00f1o, L., Vallecillo, A.: On the assessment of generative ai in modeling tasks: an experience report with chatgpt and uml. Softw. Syst. Model. 22, 781\u2013793 (2023)","journal-title":"Softw. Syst. Model."},{"issue":"3","key":"17_CR7","first-page":"1","volume":"18","author":"HG Fill","year":"2023","unstructured":"Fill, H.G., Fettke, P., K\u00f6pke, J.: Conceptual modeling and large language models: impressions from first experiments with chatgpt. Enterprise Model. Inf. Syst. Architect. 18(3), 1\u201315 (2023)","journal-title":"Enterprise Model. Inf. Syst. Architect."},{"key":"17_CR8","doi-asserted-by":"crossref","unstructured":"Hoppe, N., H\u00e4rting, R.C., Rahmel, A.: Potential Benefits of Artificial Intelligence in Healthcare, pp. 225\u2013249 (2022)","DOI":"10.1007\/978-3-031-11170-9_9"},{"key":"17_CR9","doi-asserted-by":"crossref","unstructured":"Imai, M., Kita, S.: The sound symbolism bootstrapping hypothesis for language acquisition and language evolution. Philos. Trans. R. Soc. B 369(1651) (2014)","DOI":"10.1098\/rstb.2013.0298"},{"key":"17_CR10","doi-asserted-by":"crossref","unstructured":"Kim, M., Zimmermann, T., DeLine, R., Begel, A.: The emerging role of data scientists on software development teams. In: Proceedings of the 38th International Conference on Software Engineering, pp. 96\u2013107 (2016)","DOI":"10.1145\/2884781.2884783"},{"key":"17_CR11","unstructured":"Nonaka, I., Takeuchi, H.: The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press (2011)"},{"key":"17_CR12","unstructured":"Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C.L., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., Schulman, J., Hilton, J., Kelton, F., Miller, L., Simens, M., Askell, A., Welinder, P., Christiano, P., Leike, J., Lowe, R.: Training language models to follow instructions with human feedback. https:\/\/arxiv.org\/pdf\/2203.02155 (2022)"},{"key":"17_CR13","unstructured":"Radford, A., Narasimhan, K., Salimans, T., Sutskever, I.: Improving language understanding by generative pre-training. https:\/\/cdn.openai.com\/research-covers\/language-unsupervised\/language_ understanding_ paper.pdf (2018)"},{"key":"17_CR14","unstructured":"Carey, S.: The Origin of Concepts. Oxford University Press (2011)"},{"key":"17_CR15","doi-asserted-by":"crossref","unstructured":"Takeuchi, H., Yamamoto, S.: Business ai alignment modeling based on enterprise architecture. In: Proceedings of the 11th KES International Conference on Intelligent Decision Technologies (Springer Smart Innovation, Systems and Technologies vol. 143), pp. 155\u2013165 (2019)","DOI":"10.1007\/978-981-13-8303-8_14"},{"key":"17_CR16","doi-asserted-by":"crossref","unstructured":"Takeuchi, H., Yamamoto, S.: Method for assessing the applicability of ai service systems. In: Proceedings of the 13th KES International Conference on Human Centered Intelligent Systems (Springer Smart Innovation, Systems and Technologies vol. 189), pp. 323\u2013334 (2020)","DOI":"10.1007\/978-981-15-5784-2_26"},{"key":"17_CR17","unstructured":"Transmitter, I.: 10 users of ai in everyday life. https:\/\/transmitter.ieee.org\/10-uses-of-ai-in-everyday-life\/"},{"issue":"1","key":"17_CR18","first-page":"255","volume":"8","author":"S Yamamoto","year":"2008","unstructured":"Yamamoto, S., Kanbe, M.: Knowledge creation by enterprise sns. Int. J. Knowl., Cult. Change Manag. 8(1), 255\u2013264 (2008)","journal-title":"Int. J. Knowl., Cult. Change Manag."}],"container-title":["Smart Innovation, Systems and Technologies","Human Centred Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-8598-8_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,16]],"date-time":"2025-01-16T08:07:18Z","timestamp":1737014838000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-8598-8_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819785971","9789819785988"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-8598-8_17","relation":{},"ISSN":["2190-3018","2190-3026"],"issn-type":[{"type":"print","value":"2190-3018"},{"type":"electronic","value":"2190-3026"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"17 January 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"KES-HCIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International KES Conference on Human Centred Intelligent Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Madeira","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"keshcis12024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/hcis-24.kesinternational.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}