跳到主要內容

臺灣博碩士論文加值系統

(216.73.216.110) 您好!臺灣時間:2025/09/25 07:51
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:余承翰
研究生(外文):CHEN-HAN WU
論文名稱:應用模糊關聯法則於企業人才甄選之研究
論文名稱(外文):A Study of Enterprise Personnel Selection using Fuzzy Association Rule
指導教授:陳振東陳振東引用關係
指導教授(外文):CHEN-TUNG CHEN
學位類別:碩士
校院名稱:大葉大學
系所名稱:資訊管理學系碩士班
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2005
畢業學年度:93
語文別:中文
論文頁數:96
中文關鍵詞:人才甄選模糊理論資料探勘關聯法則
外文關鍵詞:Personnel selectionFuzzy sets theoryData miningAssociation rule.
相關次數:
  • 被引用被引用:7
  • 點閱點閱:262
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:2
身處現今競爭激烈的商業環境中,企業逐漸體認唯有掌握人力資源,才能獲取持續性的競爭優勢。因此,有效的人力資源管理已成為企業維持市場競爭力的重要指標之一。
人才任用具有對人力「擇優汰劣」的作用,其中人才甄選是從應徵者中挑選有能力和適當人選,以增進企業的競爭力故對企業組織極為重要。然而,企業組織一旦挑選到不適合的人才,將造成人力的浪費與成本的增加。因此,有效選才實為企業組織之一重要的研究課題。
為此,本研究主要針對人才甄選問題,結合模糊理論與關聯法則,運用模糊關聯法則的演算法,提出一個人才甄選決策的分析模式,來尋找出在職期間穩定度較高的員工。為了驗證本研究所提出之人才甄選決策分析之可行性,本研究開發一個人才甄選決策分析系統,同時輔以某企業之實際資料進行驗證分析。經由本研究所得之人才屬性能力的關聯法則,提供給企業作為人才甄選時的參考依據,將有利於協助企業就人力資源進行規劃及有效管理,以求達成提昇人力資源與企業利潤之目標。
Recently, the enterprise gradually realizes that the good human resource, is the key factor to gain the competitive advantage. Therefore, the human resource management has become the most important work for enterprise to maintain the strength of market competition.
Under this situation, how to find or select the good employee is the first challenge for enterprise. In general, personnel selection is usually to review his applicant and judge his ability to match the job. In fact, if the enterprise can not choose the suitable talented person that it will create the waste of manpower and increase the management cost.
It is difficult to find the suitable person form review the applicants. In the personnel selection process, the subject judgement of managers are usually fuzziness. Therefore, the aim of this study is to combine the fuzzy sets theory with association rule, to look for suitable person with the higher steady degree. In order to prove that the proposed method is feasible, a case study is implemented in this study. According to the result of case study, the average accuracy rate is up to 71% for predicting the steady degree of employees.
封面內頁
簽名頁
授權頁 iii
中文摘要 iv
英文摘要 v
誌謝 vi
目錄 vii
圖目錄 ix
表目錄 x

第一章 緒論 1
第一節 研究背景 1
第二節 研究動機 2
第三節 研究目的 3
第四節 研究流程 5
第二章 文獻探討 7
第一節 人才甄選 7
第二節 模糊理論 14
第三節 資料探勘 22
第三章 研究方法 26
第一節 關聯法則 26
第二節 模糊關聯法則 29
第三節 範例說明 31
第四節 人才甄選決策分析流程 37
第四章 系統開發與實證分析 38
第一節 系統建構環境 38
第二節 系統畫面說明 39
第三節 實證分析 41
第四節 問題探討 58
第五章 結論與建議 60
第一節 結論 60
第二節 後續研究與建議 61
參考文獻 63
附錄 69
[1]方世榮編譯,現代人力資源管理,華泰書局,民國90年。
[2]吳秉恩,分享式人力資源管理,翰盧圖書出版有限公司,民國88年。
[3]張火燦,策略性人力資源管理,初版,揚智出版社,民國85年。
[4]黃英忠,現代人力資源管理,再版,華泰書局,民國84年。
[5]黃英忠,人力資源管理,三民書局,民國86年。
[6]黃英忠、曹國雄、黃同圳、張火燦、王秉鈞,人力資源管理,華泰書局,民國87年。
[7]Agrawal, R., Imilienski. T. and Arun. S, ”Mining association rules between sets of items in large databases,” In Proceedings of ACM SIGMOD International Conference on Management of Data,Vol.22, pp. 207-216, 1993.
[8]Agrawal, R. and R. Srikant, ”Fast algorithm for mining association rules,” In Proceedings of the 20th International Conference on Very Large Databases, pp. 487-499, 1994.
[9]Ashforth, B. and F. Mael, ”Social identity theory and the organization,”Academy of Management Review, Vol.14, pp.20-39, 1989.
[10]Bugarin, A.J. and S. Barro, ”Reasoning with truth values on compacted fuzzy chained rules,” IEEE Transaction on System, Vol. 28, pp.34-46, 1998.

[11]Chen, S.M., ”A fuzzy reasoning approach for rule-based systems based on fuzzy logics,” IEEE Transaction on System, Vol. 26, pp.769-778, 1996.
[12]Cohen, Y. and J. Pfeffer, ”Organization hiring standards,” Administrative Science Quarterly, Vol.32, pp.1-24, 1986.
[13]Dubois, D. and H. Prade, Fuzzy sets and systems:theory and applications, Academy Press, 1980.
[14]Eder, R., and R. Buckley, The employment interview: An interactionist perspective, Resarch in Personnel and human resources management, Ferris, G. and k. Rowland(Eds), pp.75-107,1988.
[15]Fayyad, U., G. P. Shapiro and P. Smyth , ”From data mining to knowledge discovery in database,” AI magazine, Vol.17, pp.37-54, 1996.
[16]Ferris, G., M.Buckley and G. Allen ,”Promotion systems in organization,” Human Resource Planning, Vol.15, pp.47-68 , 1992.
[17]Han, J. and M. Kamber, Data Mining : Concepts and Techniques, John Wiley & Son, 2001.
[18]Heneman Ⅲ, H., D. Schwab, J. Fossum and L.Dyer, Person/human resource management, IL:Irwin, 1989.
[19]Herriot, P., Selection as a social process, Advances in selection and assessment, Smith, M. and Robertson(Eds), pp.171-188, 1989.
[20]Hong, T. P., K.Y. Lin and S. L. Wang , ”Fuzzy data mining for interesting generalized association rules,” Fuzzy Sets and Systems 138 , pp. 255–269 , 2003.
[21]Hu, Y.C., J.S. Hu, R.S. Chen and G.H. Tzeng, ”Assessing weights of product attributes from fuzzy knowledge in a dynamic environment,” European Journal of Operational Research, Vol. 154, pp.125-143, 2004.
[22]Hu, Y.C., R.S. Chen and G.H. Tzeng, ”Mining fuzzy association rules for classification problems,” Computers and Industrial Engineering, Vol. 43, pp.735-750, 2002.
[23]Ishibuchi, H., K. Nozaki and H. Tanaka, ”Distributed representation of fuzzy rules and its application to pattern classification,” Journal of Fuzzy Sets and Systems, Vol.52, pp.21-32 , 1992.
[24]Ishibuchi, H., K. Nozaki, N. Yamamoto and H. Tanaka , ”Selecting fuzzy if-then rules for classification problems using genetic algorithms,” IEEE Transcation on FuzzySystems , Vol.3, pp.260-270, 1995.
[25]Ishibuchi, H., T. Nakashima and T. Yamamoto, ”Fuzzy association rules for handling continuous attributes,” Proceedings of IEEE International Symposium on Industrial Electronics, Vol.1, pp.118-121, 2001.
[26]Ishibuchi, H., T. Yamamoto and T. Nakashima, ”Fuzzy data mining: effect of fuzzy discretization,” Proceedings of the 1st IEEE International Conference on Data Mining, pp.241-248, 2001.
[27]Kaufmann, A. and M.M. Gupta, Introduction to fuzzy arithmetic :theory and application, Van Nostrand Reinhold, New York, 1991 .
[28]Kim,S.M., J.D. Kim, J.H. Hong, D.W. Nam, D.H. Lee and J.Y. Lee, A System for Association Rule Finding from an Internet Portal Site, 2000.
[29]Kleissner, C., ”Data mining for the enterprise,” Proc of the Thirty-First Hawaii International Conference, Vol. 7, pp.295-304, 1998.
[30]Lee, C. C., ”Fuzzy logic in control systems: fuzzy logic controller, Part II,” IEEE Transactions on Systems, Vol.20, pp. 419-435, 1990.
[31]Michael, J.A. and G. Linoff, Data Mining Technique: for Marketing, Sales and Customer Support, Wiley Computer Publishing, New York, 1997.
[32]Mills, D.,”Seniority versus ability in promotion decisions, ”Industrial and Labor Relation Review, Vol.38, pp.421-425, 1985.
[33]Mitra, S., S.K. Pal and P. Mitra , ”Data mining in soft computing framework: A survey,” IEEE Transactions on Neural Networks , Vol.13 , pp3-14 , 2002.
[34]Robertson, I. and M. M. Smith, Personnel selection methods, Advances in selection and assessment, pp.89-112, 1989.
[35]Rynes, S.L., R.D. Bretz and B. Gerhart, ”The importance of recruitment in job choice:A different way of looking, ” Personnel Psychology, Vol.44, pp.487-521, 1991.
[36]Schuler, R. S., Strategic Human Resource Management: Linking the People with the Strategic Needs of the Business, Organizational Dynamic, pp.18-32, 1992.
[37]Simoudis, E., ”Reality check for data mining,” IEEE Expert, Vol.11 , pp.26-33, 1996.
[38]Smither, J.W., R.R. Reiley, R.E. Millsap, K. Pearlman and R.W. Stoffey, ”Applicant reactions to selection procedures, ” Personnel Psychology, Vol.46, pp.49-76, 1993.
[39]Tichy, N. M., C.J. Fombrun and M.A. Devanna, ”Strategic human resource management,” Sloan Management Review, Winter,Vol.23, pp.47-61, 1982.
[40]Uehara, K. and M. Fujise, ”Fuzzy inference based on families of α-level sets,”IEEE Transaction on Fuzzy Systems, Vol. 1, pp.205-221, 1993.
[41]Ulrich, D., ”Measuring human resources: an overview of practice and a prescription for results,” Human Resource Management, Vol.36, pp.303-320, 1997.
[42]Vandenberg, R. and V. Scarpello, ”The matching model:An examination of the process underlying realistic job previews, ” Journal of Applied Psychology, Vol.75, pp.60-67, 1990.
[43]Wright, P.M. and G.C. McMahan, ”Theoretical perspectives for strategic human resource management,” Journal of Management, Vol.18, pp.295-320, 1992.
[44]Yuan, K., Fuzzy Sets and Fuzzy Logic–Theory and Applications, Prentice Hall, 1995.
[45]Zadeh, L.A., ”The concept of a linguistic variable and its application to approximate reasoning I, II, III,” Information Science, Vol.8,pp.199-251,pp.301-357, Vol.9,pp. 43-80, 1975.
[46]Zadeh, L.A., ”Fuzzy Sets, ” Information and Control, Vol.8, pp.338-353, 1965.
[47]Zhang, C. and S. Zhang ,Association rule mining: model and algorithms, Springer-Verlag Berlin Heidelberg, New York, 2002.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
1. 范文芳(2001)。改進語文教學培養思辨能力。新竹師範學院語文學報。7。93-111。
2. 洪蘭(2002)。多元智慧。文教新潮。7(2)。6-8。
3. 洪蘭(2002)。多元智慧。文教新潮。7(2)。6-8。
4. 幸曼玲(2003)。語文教學的困境與省思。教師天地。126。57-64。
5. 幸曼玲(2003)。語文教學的困境與省思。教師天地。126。57-64。
6. 林秀桂(2002)。國語文教學輔導現況。教師之友。43(4)。23-25。
7. 林秀桂(2002)。國語文教學輔導現況。教師之友。43(4)。23-25。
8. 吳思華、陳靜瑤(2005)。競爭力背後的創造力-以教育部顧問室「創造力教育中程發展計劃」為例談創造力教育。教育研究月刊。133。5-10。
9. 吳思華、陳靜瑤(2005)。競爭力背後的創造力-以教育部顧問室「創造力教育中程發展計劃」為例談創造力教育。教育研究月刊。133。5-10。
10. 吳明雄、朱珮妤(2004)。開闢創造力的學習空間-由學習理論談創造利教育。師說。178。42-45。
11. 吳明雄、朱珮妤(2004)。開闢創造力的學習空間-由學習理論談創造利教育。師說。178。42-45。
12. 吳靜吉、林偉文、林士郁、陳秋秀、曾敬梅、王涵儀、徐悅淇(2001)。國際創造力發展的趨勢。資優教育研究。2(1)。1-26。
13. 吳靜吉、林偉文、林士郁、陳秋秀、曾敬梅、王涵儀、徐悅淇(2001)。國際創造力發展的趨勢。資優教育研究。2(1)。1-26。
14. 吳靜吉(2002)。華人學生創造力的發展與培育。應用心理研究。15。17-42。
15. 吳靜吉(2002)。華人學生創造力的發展與培育。應用心理研究。15。17-42。