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研究生: Ratih Nur Esti Anggraini
Ratih - Nur Esti Anggraini
論文名稱: Conflict of Interest (COI) Detector in Reviewer Recommendation System using Potential Friendship Finder
Conflict of Interest (COI) Detector in Reviewer Recommendation System using Potential Friendship Finder
指導教授: 李漢銘
Hahn-Ming Lee
口試委員: Tyng-Ruey Chuang
Tyng-Ruey Chuang
Wei-Chung Teng
Wei-Chung Teng
Tien-Ruey Hsiang
Tien-Ruey Hsiang
Jan-Ming Ho
Jan-Ming Ho
學位類別: 碩士
Master
系所名稱: 電資學院 - 資訊工程系
Department of Computer Science and Information Engineering
論文出版年: 2012
畢業學年度: 100
語文別: 英文
論文頁數: 51
中文關鍵詞: confllict of interestreviewer recommendation systempotential link finder.
外文關鍵詞: confllict of interest, reviewer recommendation system, potential link finder.
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Conflict of Interest (COI) detection has become a significant issue in reviewer recommendation system because it can cause bias in the actor decision during reviewing process. Therefore, it is important to find relationships between actors in the network to avoid COI. Unfortunately, due to incomplete information in the network or for privacy reason, we can not detect all of those relationship.
In this thesis, we proposed Conflict of Interest (COI) Detector in Reviewer Recommendation System. Our approach can detect four types of COI: 1) COI in Coauthorship; 2) COI in Potential Friendship; 3) COI in Academic Ranking; and 4) COI in Institution. Potential Friendship Finder intends to find potential link between nodes in the network. It also can be used to suggest future collaboration to the expert.
The experiment results show that our proposed approach have a high recal rates and can detected more than 95% COI from a list of reviewers in recommendation system. The system also can adapt well to various network topologies.


Conflict of Interest (COI) detection has become a significant issue in reviewer recommendation system because it can cause bias in the actor decision during reviewing process. Therefore, it is important to find relationships between actors in the network to avoid COI. Unfortunately, due to incomplete information in the network or for privacy reason, we can not detect all of those relationship.
In this thesis, we proposed Conflict of Interest (COI) Detector in Reviewer Recommendation System. Our approach can detect four types of COI: 1) COI in Coauthorship; 2) COI in Potential Friendship; 3) COI in Academic Ranking; and 4) COI in Institution. Potential Friendship Finder intends to find potential link between nodes in the network. It also can be used to suggest future collaboration to the expert.
The experiment results show that our proposed approach have a high recal rates and can detected more than 95% COI from a list of reviewers in recommendation system. The system also can adapt well to various network topologies.

Abstracti Acknowledgementsi Table of Contentsii List of Figuresiv List of Tablesv CHAPTER 1Introduction1 1.1Motivation2 1.2Challenges3 1.3Related Work4 1.4Contribution/Goals4 1.5Outlines of the Thesis5 CHAPTER 2Background6 2.1Reviewer Recommendation System6 2.2Conflict of Interest7 2.3Social Network Analysis8 2.4Link Prediction9 2.4.1Similarity Based Algorithms10 2.4.2Maximum Likelihood Methods12 2.4.3Probabilistic Models13 CHAPTER 3System Architecture14 3.1Notation Definition14 3.2System Architecture14 3.2.1Coauthorship COI Finder15 3.2.2Potential Friendship COI Finder18 3.2.3Academic Ranking COI Finder20 3.2.4Institution COI Finder22 3.3System GUIs24 CHAPTER 4Experiments26 4.1Experiment Setup26 4.2Dataset27 4.3Evaluation Methodology27 4.4Experiment Results and Discussions28 CHAPTER 5Conclusion and Further Work32 5.1Conclusion32 5.2Further Work33 References34

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