現今的雇傭行為常以網路服務作為協助，求職者 ( Job seeker ) 以及雇傭者 ( Recruiter ) 透過就業網站 ( Job portal ) 所提供的服務來找尋可能的對象。透過就業網站的服務，求職者以及雇傭者能夠輕易地接觸到來自許多可能對象的資訊，大量的資訊在這些使用者之間傳佈、匹配 ( Matching )。目前就業網站提供的多數服務著重在資訊傳佈及過濾，著重在比對單一求職者以及雇傭者的資訊以提供適性 ( Compatibility ) 建議的服務則較為稀少。

求職者以及雇傭者需要逐一檢視可能對象的資訊，並匹配雇傭者的需求 ( Requirement ) 以及求職者的專業能力 ( Expertise ) 資訊適性，以確認自己與對象的匹配程度。而隨著就業網站的使用者人數持續攀升，需要花費在進行比對上的勞力也會增加。另外，求職者以及雇傭者之間僅靠著對方提供的資訊進行匹配，雙方並沒有實際的共通檢定標準，求職者在匹配的過程中存在著對於雇傭者的需求誤解的可能。基於這些不便，可以看到就業網站在資訊匹配上的不足之處。就業網站需要在工作配對 ( Job Matching Event ) 上提供更具體的協助，以滿足使用者的需要。

這篇論文建立了一個幫助進行資訊配對的系統框架。這個框架透過引入評量指標 ( Criteria ) 作為雇傭者以及求職者間的共享標準，將雇傭者的需求轉化為可測量的指標，並從求職者的資材中界定其專業能力對於指標的符合程度。透過將雙方的需求以及能力放在同樣的標準下進行匹配，並且讓雙方共享匹配結果以確保彼此的適性，這個框架將有助於減低匹配時的勞力花費，並確保雙方對於彼此的適性有著共同的認知。為了調查此論文提出之框架的有效性，這篇論文進行了一則個案研究。結果顯示了在框架中目前實現的評量指標能夠涵蓋 28 % 求職者用以檢定其專業能力的指標。而透過此框架的可拓展性 ( Extension )，預估能夠涵蓋的範圍則可到達 58 %。另外，在此研究中也顯示了框架能夠分辨出在同一個軟體開發團隊中不同成員的專業能力。

Job seekers and recruiters often turn to online recruitment services provided by job portals. Through these job portals, massive information is exchanged and matched between job seekers and recruiters. Job portals provide more services for information exchanging or filtering, but with less support for job matching between job seeker and recruiter.

Users, including the job seekers and recruiters, have to match the information between job requirements and seeker expertise manually to identify potential candidates. It further leads challenges in dealing with large amount of job matching events and performing job matching with evidence in an event. While the amount of users on job portals increase, the effort spent on job matching will also raise rapidly. Moreover, without common criteria to comprehend the job requirements, it is possible for job seekers to misunderstand the requirement.

To resolve the challenges, this work establishes an evidence sharing framework for automatic, evidential job matching between job seekers and recruiters. The framework extracts evidences from software artifacts, expressing job seeker’s expertise and recruiter’s requirement in a shared model. Job seekers and recruiters can ensure their compatibility through the match report provided.

A case study is conducted to investigate the effectiveness of the framework in realistic conditions. The result shows that 28% of criteria suggested by participants are directly covered by the criteria currently implemented in the framework. The coverage can be enhanced to 58% by extending criteria. Also, the framework can distinguish the expertise of each member in the same project team.

Cover i
Oral presentation document ii
Chinese version . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
English version . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
Abstract (Chinese) iv
Abstract (English) vi
Acknowledgments vii
List of Figures x
List of Tables xi
Chapter 1. Introduction 1
Chapter 2. Related Work and Background 3
2.1 Preserved Project Memory for Developer Expertise Recommendation . . 3
2.2 ePortfolio for Personal Experience Exhibition . . . . . . . . . . . . . . . 4
2.3 A Survey of Existing Job Portals . . . . . . . . . . . . . . . . . . . . . . 4
2.3.1 Goals and Survey Scope . . . . . . . . . . . . . . . . . . . . . . . 4
2.3.2 Definition of Job Matching Event . . . . . . . . . . . . . . . . . . 5
2.3.3 Categorization of Job Requirements . . . . . . . . . . . . . . . . . 6
2.3.4 Categorization of Job Seekers' Information . . . . . . . . . . . . . 7
2.3.5 Job Seeking Process . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.3.6 Functionalities for Job Candidate Recommendation . . . . . . . . . 12
2.3.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Chapter 3. Evidence Sharing Framework 17
3.1 Principles of Framework . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.2 Framework Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3.3 Modeling Representative Evidences from Job Seeker’s Artifact . . . . . 21
3.3.1 Criteria for Java and Python . . . . . . . . . . . . . . . . . . . . . 22
3.3.2 Criteria for SVN . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.4 Modeling Recruitment Criteria . . . . . . . . . . . . . . . . . . . . . . . 24
3.5 Matching between Recruitment Criteria and Evidence . . . . . . . . . . . 25
Chapter 4. Case Study 27
4.1 Study Setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.2 Coverage Investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.2.1 Research Setting . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.2.2 Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
4.2.3 Criteria Coverage with Extension . . . . . . . . . . . . . . . . . . 31
4.3 Correlation Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . 33
4.3.1 Research Setting . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
4.3.2 Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
Chapter 5. Conclusion 37
References 38

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