楊博;趙鵬飛;

• 1:吉林大學計算機科學與技術學院
• 2:吉林大學符號計算與知識工程教育部重點實驗室

摘要(Abstract)：

推薦是解決互聯網信息過載的主要途徑之一,已被廣泛應用于電子商務等多個領域.盡管已存在多種推薦算法,建造出更加智能、更加魯棒的推薦系統仍面臨諸多尚未解決的難題,推薦方法的研究仍是智能信息處理的研究熱點.文章首先闡述了推薦方法的研究背景、研究意義,之后分別介紹了協同過濾推薦算法、基于內容的推薦算法、基于圖結構的推薦算法和混合推薦算法,分析了各類算法的優點與不足,最后總結了主要的評價方法以及面臨的主要問題,提出了改進的方法和未來可能的研究方向.

關鍵詞(KeyWords)： 信息過載;推薦系統;協同過濾;信息檢索;數據挖掘;機器學習

Abstract:

Keywords:

基金項目(Foundation): 國家自然科學基金(6087314960973088);; 中央高�；�本科研業務費專項資金(200903177)

作者(Author): 楊博;趙鵬飛;

Email:

DOI:

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