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    Title: 合作式個人化推薦系統之進階技術研究及其應用 (II)
    Other Titles: The Research of Advanced Techniques and Their Applications for a Collaborative Personalized Recommendation System
    Authors: 陳良弼
    Contributors: 國立政治大學資訊科學系
    行政院國家科學委員會
    Keywords: 合作式個人化推薦系統
    Date: 2010
    Issue Date: 2012-11-12 11:05:03 (UTC+8)
    Abstract: 伴隨著資訊科技之發展,各種形式的物件在網際網路上迅速的累積,資訊過量已成為使用者主要的負擔。因此,如何在大量的資料中,精確地推薦有用的資訊給使用者,即成為極具挑戰的研究課題。合作式推薦是其中一個解決資訊過量的方法;然而,隨著應用規模的成長,現階段合作式推薦系統所面臨的資料型態、處理模式與處理規模,都與過去單純的資料環境有著極大的不同,也導致現有技術有其侷限性。為了克服該問題,本計畫以三年為期研發一下世代合作式推薦系統。  在本年度計畫執行過程中,我們已完成具&;#63847;確定性資&;#63934;&;#63749;&;#63946;之&;#63898;續型機&;#63841;天際線查詢、考慮範圍查詢下的動態天際線及尋找影響力最大化的領導者之研究項目,並發表於國際一流會議。本期中報告茲就本年度所完成的研究成果進行報告。
    With rapid growth of the Internet technology, information overloading starts to be a chal-lenge. Therefore, efficient and effective ap-proaches to assist users to precisely get the useful information from massive datasets are needed. The collaborative recommendation mechanism is a popular solution to solve this problem. However, with the growth of the scale of applications, nowadays collaborative recommendation systems have to deal with dynamic and fast growing environments, in which the existing techniques become ineffi-cient and ineffective for high-quality recom-mendation results. Therefore, the advanced techniques for collaborative recommendation become important research issues, worth fur-ther studying. In this progress report, three research results we achieved in this year are presented, including 1) maintaining conti-nuous probabilistic skylines over uncertain streams, 2) dynamic skylines considering range queries, and 3) discovering k leaders with influence maximization.
    Relation: 應用研究
    學術補助
    研究期間:9908~ 10007
    研究經費:1696仟元
    Data Type: report
    Appears in Collections:[資訊科學系] 國科會研究計畫

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