保險業孤兒保單業務員推薦系統

Chia-Hsin Shen; 沈家妡

請用此 Handle URI 來引用此文件： http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/82296

完整後設資料紀錄

DC 欄位	值	語言
dc.contributor.advisor	曹承礎(Seng-Cho Chou)
dc.contributor.author	Chia-Hsin Shen	en
dc.contributor.author	沈家妡	zh_TW
dc.date.accessioned	2022-11-25T06:35:13Z	-
dc.date.copyright	2021-11-12
dc.date.issued	2021
dc.date.submitted	2021-09-14
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Algorithm AS 136: A k-Means Clustering Algorithm. Journal of the Royal Statistical Society, Series C. 1979, 28 (1): 100–108. JSTOR 2346830. [34] Peter J. Rousseeuw (1987). “Silhouettes: a Graphical Aid to the Interpretation and Validation of Cluster Analysis”. Computational and Applied Mathematics 20: 53–65. doi:10.1016/0377-0427(87)90125-7. [35] Leonard Kaufman; Peter J. Rousseeuw. Finding groups in data : An introduction to cluster analysis. Hoboken, NJ: Wiley-Interscience. 1990: 87. ISBN 9780471878766. doi:10.1002/9780470316801 [36] Samiton Pangellaha, Basuki Wibawa, Robinson Situmorang, (2019). Developing Learning Module “Smart Communication with Prospects” for Life Insurance Agents. International Journal of Innovation, Creativity and Change. www.ijicc.net Volume 6, Issue 2, 2019 [37] Turner, J.H.. (2008). An analysis of factors affecting life insurance agent sales performance. Academy of Marketing Studies Journal. 12. 71-80.
dc.identifier.uri	http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/82296	-
dc.description.abstract	在台灣保險產業相當重要，而保險業務員作為保險公司跟客戶之間的橋樑，扮演相當重要的角色，然而保險業務員的離職率高，使得孤兒保單不斷出現，本研究主要目的是透過業務員以及客戶的資訊，分析保險業務員的樣態，並建構基於機器學習方法的保險業務員推薦系統，透過推薦適合的業務員給孤兒保單客戶，希望提高客戶的再購率、業務員跟客戶的接觸率，以及減少孤兒保單需要再次分配業務員的情況。而根據推薦結果可以觀察到，本研究提出的模型在再購率、接觸率以及再調撥率都有良好的表現。	zh_TW
dc.description.provenance	Made available in DSpace on 2022-11-25T06:35:13Z (GMT). No. of bitstreams: 1 U0001-1409202112470200.pdf: 2172546 bytes, checksum: acbd3df107f68c3d264c42f78802026b (MD5) Previous issue date: 2021	en
dc.description.tableofcontents	口試委員會審定書 i 誌謝 ii 中文摘要 iii ABSTRACT iv 目錄 v 圖目錄 vii 表目錄 viii 第一章、緒論 1 第一節、研究背景與動機 1 第二節、研究目的 3 第二章、文獻探討 4 第一節、保險業務員 4 第一項、業務員業績 4 第二項、服務 5 第三項、業務員特徵的影響 5 第四項、業務員跟客戶的關係 5 第二節、協同過濾（Collaborative Filtering） 6 第一項、以記憶體為基礎的過濾（Memory Based Collaborative Filtering） 6 第二項、以模型為基礎的過濾（Model Based Collaborative Filtering） 7 第三章、研究方法 9 第一節、名詞定義 9 第二節、資料集 13 第三節、資料前處理 19 第四節、業務員推薦模型 22 第四章、研究結果與分析 26 第一節、業務員分群結果 26 第二節、比較基準 34 第三節、推薦結果觀察指標 36 第四節、推薦結果與分析 37 第五章、結論與未來展望 43 第一節、結論 43 第二節、未來展望 44 參考文獻 46 附錄 50
dc.language.iso	zh-TW
dc.subject	推薦系統	zh_TW
dc.subject	保險業	zh_TW
dc.subject	業務員	zh_TW
dc.subject	孤兒保單	zh_TW
dc.subject	機器學習	zh_TW
dc.subject	recommendation system	en
dc.subject	insurance industry	en
dc.subject	life insurance agent	en
dc.subject	orphan policy	en
dc.subject	machine learning	en
dc.title	保險業孤兒保單業務員推薦系統	zh_TW
dc.title	Insurance agent recommendation system of orphan policies in insurance business	en
dc.date.schoolyear	109-2
dc.description.degree	碩士
dc.contributor.oralexamcommittee	陳建錦(Hsin-Tsai Liu),盧信銘(Chih-Yang Tseng)
dc.subject.keyword	保險業,業務員,孤兒保單,機器學習,推薦系統,	zh_TW
dc.subject.keyword	insurance industry,life insurance agent,orphan policy,machine learning,recommendation system,	en
dc.relation.page	51
dc.identifier.doi	10.6342/NTU202103162
dc.rights.note	未授權
dc.date.accepted	2021-09-15
dc.contributor.author-college	管理學院	zh_TW
dc.contributor.author-dept	資訊管理學研究所	zh_TW
dc.date.embargo-lift	2026-09-14	-
顯示於系所單位：	資訊管理學系

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