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Collaborative Filtering in Recommendation Systems with Medical Applications
瀏覽次數:日期:2020-12-21編輯:信科院 科研辦

報告人:Zidong Wang,英國倫敦Brunel University講席教授,歐洲科學院院士,IEEE Fellow

報告時間:202012月21日 (星期一) 晚上7:30 - 9:30

報告地點:Zoom在線會議

https://us02web.zoom.us/j/2810019605?pwd=S09LNnl5dHdXajZBbEJJOVd4TVlmUT09

Meeting ID: 281 001 9605

Passcode: HNU2020

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報告摘要:In this talk, we discuss a novel user-based collaborative filtering (CF) algorithm with improved performance for recommendation systems. The statistical information set (SIS) of individual rating data is, for the first time, employed to analyze the user rating habit, thereby facilitating the performance improvement of the CF algorithm. On the basis of the SIS, a new yet comprehensive similarity measure (SM) is proposed to quantify the distance between two users with focus on both the users' preferences on items and their rating habits. Compared with the traditional SM, our proposed SM is more general with clearer application insights in complicated situations. The developed CF algorithm makes full use of the known information of a recommendation system, which merits high prediction accuracy and wide application potential. The developed CF algorithm is applied to a real-world disease (Friedreich's ataxia) assessment system, where both the effectiveness and the superiority of our proposed algorithm are demonstrated.

 

報告人簡介:王子棟,現任英國倫敦Brunel University講席教授,歐洲科學院院士,IEEE Fellow,Neurocomputing主編,國際系統科學雜志執行主編。多年從事控制理論、信號處理、生物信息學方面研究,在SCI刊物上發表國際論文六百余篇?,F任或曾任十二種國際刊物的主編、副編輯或編委。曾任旅英華人自動化及計算機協會主席、東華大學長江學者講座教授、清華大學國家級專家。


邀請人:李肯立

 

聯系人:陳建國  

 

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