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題名 專家社群網絡上的團隊形成與團隊績效預測
作者 沈錳坤
貢獻者 資訊科學系
關鍵詞 團隊形成;社群網絡;合作網絡;專家查詢
Team Formation; Social Networks; Collaborative Networks; Expertise Query
日期 2013
上傳時間 8-Dec-2017 15:07:50 (UTC+8)
摘要 團隊形成是現代組織理論中重要的議題。成功的團隊不僅仰賴團隊成員的能力,也取決於團隊成員的合作關係。換句話說,給定任務所需求的能力,在組織團隊時,所邀集的團隊成員不僅必須具備需求能力,同時成員彼此之間也必須能溝通合作。因此本計劃研究專家社群網絡上的團隊形成。給定一個專家社群網絡,其中每個節點代表擁有技能的專家、每個邊代表專家之間的溝通成本,團隊形成的問題就是從中找到候選專家,不僅符合任務所需的能力要求,而且候選專家間的溝通成本越低越好。本計劃延伸基本的團隊形成問題,將每個需求能力所需的最少專家數列入考慮。我們研究有效率的延伸團隊形成演算法。我們以DBLP的資料實驗證實我們所提出的演算法無論在效率與效果上都有較好的表現。
Team formation is essential in the field of organization theory. A successful project relies on not only the expertise of participated members but also on the communication and collaboration between them. In other words, to form a team of experts for a given task consisting of some skills, it is critical to find a set of persons whose professional skills satisfy the requirement of given task and are able to communicate effectively with each other. This project investigates the team formation problem. Given a social network in which each vertex represents an expert in some skills and each weighted edge indicates the communication cost, the team formation problem is to find some experts from these candidates to meet the requirement of a given task and minimize the total communication cost. This project generalizes the basic team formation problem by considering the minimum number of experts required for each skill. Moreover, based on the team formation algorithm, this project investigates the context-based people search for social network service which aims at finding an individual not only by the name of the target, by also by the social contexts of the target. Experimental results on the DBLP network show that the teams composed by the proposed methods have better performance in both effectiveness and efficiency.
關聯 執行起迄:2013/08/01~2014/07/31
102-2221-E-004-007
資料類型 report
dc.contributor 資訊科學系zh_Tw
dc.creator (作者) 沈錳坤zh_TW
dc.date (日期) 2013en_US
dc.date.accessioned 8-Dec-2017 15:07:50 (UTC+8)-
dc.date.available 8-Dec-2017 15:07:50 (UTC+8)-
dc.date.issued (上傳時間) 8-Dec-2017 15:07:50 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/115089-
dc.description.abstract (摘要) 團隊形成是現代組織理論中重要的議題。成功的團隊不僅仰賴團隊成員的能力,也取決於團隊成員的合作關係。換句話說,給定任務所需求的能力,在組織團隊時,所邀集的團隊成員不僅必須具備需求能力,同時成員彼此之間也必須能溝通合作。因此本計劃研究專家社群網絡上的團隊形成。給定一個專家社群網絡,其中每個節點代表擁有技能的專家、每個邊代表專家之間的溝通成本,團隊形成的問題就是從中找到候選專家,不僅符合任務所需的能力要求,而且候選專家間的溝通成本越低越好。本計劃延伸基本的團隊形成問題,將每個需求能力所需的最少專家數列入考慮。我們研究有效率的延伸團隊形成演算法。我們以DBLP的資料實驗證實我們所提出的演算法無論在效率與效果上都有較好的表現。zh_TW
dc.description.abstract (摘要) Team formation is essential in the field of organization theory. A successful project relies on not only the expertise of participated members but also on the communication and collaboration between them. In other words, to form a team of experts for a given task consisting of some skills, it is critical to find a set of persons whose professional skills satisfy the requirement of given task and are able to communicate effectively with each other. This project investigates the team formation problem. Given a social network in which each vertex represents an expert in some skills and each weighted edge indicates the communication cost, the team formation problem is to find some experts from these candidates to meet the requirement of a given task and minimize the total communication cost. This project generalizes the basic team formation problem by considering the minimum number of experts required for each skill. Moreover, based on the team formation algorithm, this project investigates the context-based people search for social network service which aims at finding an individual not only by the name of the target, by also by the social contexts of the target. Experimental results on the DBLP network show that the teams composed by the proposed methods have better performance in both effectiveness and efficiency.en_US
dc.format.extent 2144649 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) 執行起迄:2013/08/01~2014/07/31zh_TW
dc.relation (關聯) 102-2221-E-004-007zh_TW
dc.subject (關鍵詞) 團隊形成;社群網絡;合作網絡;專家查詢zh_TW
dc.subject (關鍵詞) Team Formation; Social Networks; Collaborative Networks; Expertise Queryen_US
dc.title (題名) 專家社群網絡上的團隊形成與團隊績效預測_TW
dc.type (資料類型) report