【摘要】：淘寶網(wǎng)作為電子商務(wù)時(shí)代最大的網(wǎng)上零售平臺(tái),為用戶(hù)提供越來(lái)越多的商品與服務(wù)的同時(shí),也出現(xiàn)了信息過(guò)載等一系列問(wèn)題。鑒于此,本文提出了基于商品屬性與用戶(hù)聚類(lèi)的個(gè)性化服裝推薦方法,通過(guò)用戶(hù)個(gè)人信息與對(duì)商品的評(píng)價(jià),計(jì)算用戶(hù)之間的相似度,進(jìn)行聚類(lèi)分析。與此同時(shí),將商品化整為零,通過(guò)商品屬性來(lái)計(jì)算商品的相似度,得到top-N相似列表。以此,綜合商品與用戶(hù)兩者的權(quán)重值,實(shí)現(xiàn)為用戶(hù)提供個(gè)性化的商品推薦,解決用戶(hù)面對(duì)信息過(guò)載的難題,為用戶(hù)節(jié)省精力,提高用戶(hù)的購(gòu)物體驗(yàn)。針對(duì)某一淘寶網(wǎng)店鋪,本文提出了適合的混合推薦算法,并通過(guò)搜集實(shí)際數(shù)據(jù)進(jìn)行了實(shí)證研究,對(duì)推薦結(jié)果進(jìn)行準(zhǔn)確性評(píng)價(jià)。
[Abstract]:Taobao, as the largest online retail platform in the era of electronic commerce, provides more and more goods and services to users, at the same time, there are a series of problems such as information overload and so on. In view of this, this paper proposes a personalized clothing recommendation method based on commodity attributes and user clustering, which calculates the similarity between users and makes clustering analysis through the personal information of users and the evaluation of commodities. At the same time, the commodity is divided into zero, and the similarity of goods is calculated by commodity attributes, and the top-N similarity list is obtained. In this way, the weights of both commodities and users can be synthesized to provide personalized commodity recommendation for users, solve the problem that users face information overload, save energy for users and improve their shopping experience. For a Taobao shop, this paper proposes a suitable hybrid recommendation algorithm, and through the collection of practical data for empirical research, the accuracy of the recommendation results are evaluated.
【作者單位】： 武漢大學(xué)信息管理學(xué)院;
【分類(lèi)號(hào)】：F724.6;F426.86

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 劉建國(guó);周濤;郭強(qiáng);汪秉宏;;個(gè)性化推薦系統(tǒng)評(píng)價(jià)方法綜述[J];復(fù)雜系統(tǒng)與復(fù)雜性科學(xué);2009年03期

2 三川;;CNNIC發(fā)布第35次《中國(guó)互聯(lián)網(wǎng)絡(luò)發(fā)展?fàn)顩r統(tǒng)計(jì)報(bào)告》[J];中國(guó)遠(yuǎn)程教育;2015年02期

3 王國(guó)霞;劉賀平;;個(gè)性化推薦系統(tǒng)綜述[J];計(jì)算機(jī)工程與應(yīng)用;2012年07期

4 李雪峰;劉魯;張f，

本文編號(hào)：2407151