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    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/49657
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/49657


    Title: 以語意網建構人才推薦與信任推論機制之研究— 以某國立大學EMBA人才庫為例
    A study of semantic web-based specialist recommendation & trust inference mechanism-a case of EMBA database
    Authors: 蔡承翰
    Tsai, Cheng Han
    Contributors: 楊建民
    蔡承翰
    Tsai, Cheng Han
    Keywords: 招募管道
    語意網
    人才推薦系統
    信任
    社會網絡
    recruitment channel
    semantic web
    human source recommendation system
    trust
    social network
    Date: 2009
    Issue Date: 2010-12-08 16:02:54 (UTC+8)
    Abstract: 「人」是公司中最重要的資產,而在知識密集的行業中,這樣的資產更顯得重要。由於網路技術的出現,網路人力銀行也成為另外一種人才招募的新興管道,但透過網路人力銀行所召募的人才素質並沒有傳統上透過公司員工推薦進來的人才可更進一步瞭解的好處。因此本研究透過一網路人才推薦信任制度,來加強線上人力銀行之人才篩選能力,希望透過此制度能繼續保有網路人力銀行在人才招募速度上的優勢,並能加強其篩選的能力。
    本研究針對人才招募管道進行了文獻的探討,提出一人才推薦制度,以某國立大學EMBA之人才庫,透過成員間的學經歷背景相似度,推薦出擁有相同顯性工作能力的人才。讓人才招募單位可以得到推薦的人才,並可對其作信任評價的推論。接著利用實驗來求出雛型系統的一些關鍵參數,讓雛型系統運作得更完善以及更符合使用者的需求。
    本雛型系統結合了網路人力銀行人才招募方式可快速地招募到大量員工的特點,及員工推薦人才招募方式可招募到更適切員工的特點。並透過FOAF格式的使用,將線上社會網絡的資料格式統一,有助於縮短整個人才信任推薦系統的建立時間。
    "Human Resource" is one of the most important assets of company, especially in knowledge-intensive industries. As network technologies developed, commercial job site has also become another kind of recruitment channel. But through this kind of channel, companies don’t have better chance to know new employee than traditional way. Therefore this study filters new employees by a Recommendation & Trust Inference mechanism. Hope that commercial job site would continue to keep the advantages of high efficiency in recruitment, and enhance its filtering capability at the same time.
    First, this study surveys literatures in recruitment channels. And it proposes a Recommendation & Trust Inference mechanism using a national university EMBA program member data as an example. The Recommendation mechanism recommend candidates having the same specialty by comparing their similarity of education and work experience. Furthermore, recruitment unit could use Trust Inference mechanism to get suitable candidates. Third, we conduct experiments to find the key parameters for the prototype system. Make the system able to work better and meet users’ needs.
    The prototype system combines the benefit of commercial job site which can quickly recruit a large number of employees and the feature providing more appropriate candidates for the company recommended by staff. Simultaneously by taking use of the FOAF format, we can unify the data format in online social network. The way mentioned above will effectively reduce the system set-up time.
    Reference: 1. 何丁武、邱耀漢、楊建民 (2006)。電子音樂知識本體論推薦機制與架構之研究。第十七屆國際資訊管理學術研討會論文集,中華民國資訊管理學會。
    2. 李永銘、李宗穎、陳正乾 (2006)。信任機制為基礎之即時通訊系統。第十二屆資訊管理暨實務研討會。
    3. 李永銘、陳正乾、李宗穎 (2007)。使用信任機制的部落格。第十八屆國際資訊管理學術研討會。國科會編號:NSC 94-2416-H-009-030
    4. 李誠、簡士評 (2001)。網路招募管道有效性的初步分析─以某高科技企業為例。高科技產業人力問題研討會論文集,台灣經濟發展研究中心。
    5. 呂春美、蔡承翰、楊建民 (2009)。建構人脈關聯社會網絡人才推薦系統之研究-以某國立大學EMBA人才庫為例。第十五屆資訊管理暨實務研討會。
    6. 游卓凡 (2007)。以語意化同儕網路建立產業知識管理系統。大同大學資訊工程研究所碩士論文。
    7. 楊永芳 (2002)。語意擴充式文件推薦方法之研究。國立中山大學資訊管理研究所碩士論文。
    8. 簡士評 (2001)。招募管道成效之評估。國立中央大學人力資源管理研究所碩士論文。
    9. Abdul-Rahman, A. and Hailes, S. (2000). Supporting Trust in Virtual Communities, Proceedings of the 33rd Hawaii International Conference on System Sciences.
    10. Antoniou, G. and Harmelon, F. (2008). A Semantic Web Primer (2nd ed.). Cambridge, MA: MIT Press.
    11. Berners-Lee, T., Hendler, J. and Lassila, O. (2001, May). The Semantic Web. Scientific American Magazine.
    12. Berners-Lee, T. and Fischetti, M. (1999). Weaving the Web: The original design and ultimate destiny of the World Wide Web by its inventor (1st editioned.), Harperbusiness .
    13. Bhavsar, V. C., Boley, H. and Yang, L. (2003). A weighted-tree similarity algorithm for multi-agent systems in e-business environment. Proceedings of Business Agents and the Semantic Web (BASeWEB) Workshop, Nova Scotia, Canada.
    14. Bonhard, P., Harries, C., McCarthy, J. and Sasse, M. A. (2006). Accounting for Taste: Using Profile Similarity to Improve Recommender Systems. Proceedings of the SIGCHI conference on Human Factors in computing systems, Quebec, Canada
    15. Cosley, D., Ludford, P. and Terveen, L. (2003). Studying the Effect of Similarity in Online Task-Focused Interactions. Proceedings of the 2003 international ACM SIGGROUP conference on Supporting group work, Florida, USA
    16. Finin, T., Ding, L., Zou, L. and Joshi, A. (2005). Social Networking on the Semantic Web. Learning Organization, 12(5), 418-435.
    17. Golbeck, J., Parsia, B., and Hendler, J. (2003). Trust Networks on the Semantic Web. Proceedings of Cooperative Intelligent Agents, Helsinki, Finland.
    18. Golbeck, J. (2006) Generating Predictive Movie Recommendations from Trust in Social Networks. Proceedings of the 4th International Conference on Trust Management, Pisa, Italy.
    19. Golbeck, J. (2009). Trust and Nuanced Profile Similarity in Online Social Network. ACM Transactions on the Web (TWEB), 3(4), Article No.: 12
    20. Huang, J. and FOX, M. S. (2006). An Ontology of Trust –Formal Semantics and Transitivity. Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet, New Brunswick, Canada.
    21. Kim, Y. A., Le, M. T., Lauw, H. W., Lim, E. P., Liu, H. and Srivastava, J. (2008). Building a Web Trust without Explicit Trust Rating. Proceedings of the 24th International Conference on Data Engineering Workshops, Cancún, Mexico.
    22. Marmaros, D., and Sacerdote, B. (2002). Peer and social networks in job search. European Economic Review, 46(4-5), 870-879.
    23. McDonald, D. W. (2003). Ubiquitous recommendation systems. Computer, 36(10), 111-112.
    24. Milgram, S. (1967). The small world problem. Psychology Today, 1(1), 60–67.
    25. Papagelis, M., Plexousakis, D. and Kutsiras, T. (2005). Alleviating the Sparsity Problem of Collaborative Filtering Using Trust Inferences. Proceedings of the 3rd International Conference on Trust Management, Paris, France.
    26. Rees, A. (1966). Labor economics: Effects of more knowledge. American Economic Review, 56, 559-566.
    27. Sinha, R. and Sewaringen, K. (2001) Comparing recommendations made by online systems and friends . Proceedings of DELOS-NSF Workshop: Personalisation and Recommender Systems in Digital Libraries, Dublin, Ireland
    28. Taylor, M. S. and Schmidt, D. W. (1983). A process-oriented investigation of recruitment source effectiveness. Personnel psychology, 36, 343-354.
    29. Ziegler, C. N. and Golbeck, J. (2005). Investigating Correlations of Trust and Interest Similarity – Do Birds of a Feather Really Flock Together? Decision Support System.
    參考網址
    [a]. FOAF project: The Friend of a Friend Project. Retrieved June 8, 2010, from http://www.foaf-project.org/
    [b]. FOAF project: FOAF Vocabulary Specification 0.97. Retrieved June 8, 2010, from http://xmlns.com/foaf/spec/
    [c]. Kuhlen, A. (2001). E-recruiting Experts` views on e-recruiting processes. http://www.erecruitix.com/
    [d]. Linked in. http://www.linkedin.com/
    [e]. Swoogle. http://swoogle.umbc.edu/
    [f]. Westphal, D. and Bizer, C. (2004, October). Introduction to RAP.http://www.seasr.org/wp-content/plugins/meandre/rdfapi-php/doc/tutorial/introductionToRAP.htm
    [g]. WIKIPEDIA: FOAF (software). http://en.wikipedia.org/wiki/FOAF_%28software%29
    [h]. W3Cschool. http://www.w3schools.com/
    Description: 碩士
    國立政治大學
    資訊管理研究所
    97356029
    98
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0097356029
    Data Type: thesis
    Appears in Collections:[資訊管理學系] 學位論文

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