基于上下文相似度和社會網(wǎng)絡(luò)的移動服務(wù)推薦方法
發(fā)布時間：2019-04-26 14:02
【摘要】：針對傳統(tǒng)的基于協(xié)同過濾的移動服務(wù)推薦方法存在的數(shù)據(jù)稀疏性和用戶冷啟動問題,提出一種基于上下文相似度和社會網(wǎng)絡(luò)的移動服務(wù)推薦方法(Context-similarity and Social-network based Mobile Service Recommendation,CSMSR).該方法將基于用戶的上下文相似度引入個性化服務(wù)推薦過程,并挖掘由移動用戶虛擬交互構(gòu)成的社會關(guān)系網(wǎng)絡(luò),按照信任度選取信任用戶;然后結(jié)合基于用戶評分相似度計算發(fā)現(xiàn)的近鄰,分別從相似用戶和信任用戶中選擇相應(yīng)的鄰居用戶,對目標(biāo)用戶進行偏好預(yù)測和推薦.實驗表明,與已有的服務(wù)推薦方法 TNCF、SRMTC及CF-DNC相比,CSMSR方法有效地緩解數(shù)據(jù)稀疏性并提高推薦準(zhǔn)確率,有利于發(fā)現(xiàn)用戶感興趣的服務(wù),提升用戶個性化服務(wù)體驗.
[Abstract]:Aiming at the problems of data sparsity and user cold start in traditional mobile service recommendation methods based on collaborative filtering, a mobile service recommendation method based on context similarity and social network (Context-similarity and Social-network based Mobile Service Recommendation,) is proposed. CSMSR). In this method, the context similarity of users is introduced into the personalized service recommendation process, and the social network composed of virtual interaction of mobile users is mined, and the trusted users are selected according to the degree of trust. Then, combining the nearest neighbors based on the similarity calculation of the user score, the corresponding neighbor users are selected from the similar users and trusted users, and the preference prediction and recommendation of the target users are carried out. The experimental results show that compared with the existing service recommendation methods TNCF,SRMTC and CF-DNC, the CSMSR method can effectively alleviate the data sparsity and improve the recommendation accuracy, which is beneficial to the discovery of services of interest to users and the improvement of user personalized service experience.
【作者單位】： 南京工業(yè)大學(xué)計算機科學(xué)與技術(shù)學(xué)院;復(fù)旦大學(xué);中國人民解放軍73677部隊;
【基金】：國家自然科學(xué)基金(No.61203072) 江蘇省重點研發(fā)計劃(社會發(fā)展)(No.BE2015697)
【分類號】：TP391.3
[Abstract]:Aiming at the problems of data sparsity and user cold start in traditional mobile service recommendation methods based on collaborative filtering, a mobile service recommendation method based on context similarity and social network (Context-similarity and Social-network based Mobile Service Recommendation,) is proposed. CSMSR). In this method, the context similarity of users is introduced into the personalized service recommendation process, and the social network composed of virtual interaction of mobile users is mined, and the trusted users are selected according to the degree of trust. Then, combining the nearest neighbors based on the similarity calculation of the user score, the corresponding neighbor users are selected from the similar users and trusted users, and the preference prediction and recommendation of the target users are carried out. The experimental results show that compared with the existing service recommendation methods TNCF,SRMTC and CF-DNC, the CSMSR method can effectively alleviate the data sparsity and improve the recommendation accuracy, which is beneficial to the discovery of services of interest to users and the improvement of user personalized service experience.
【作者單位】： 南京工業(yè)大學(xué)計算機科學(xué)與技術(shù)學(xué)院;復(fù)旦大學(xué);中國人民解放軍73677部隊;
【基金】：國家自然科學(xué)基金(No.61203072) 江蘇省重點研發(fā)計劃(社會發(fā)展)(No.BE2015697)
【分類號】：TP391.3
【相似文獻】
相關(guān)期刊論文 前10條
1 戴英;;基于移動互聯(lián)網(wǎng)的圖書館移動服務(wù)的探索[J];內(nèi)蒙古科技與經(jīng)濟;2013年07期
2 璐璐妹,徐尚志;手機世界的移動服務(wù)[J];數(shù)字通信;2001年08期
3 ;讓移動服務(wù)準(zhǔn)確定位[J];信息系統(tǒng)工程;2001年07期
4 袁正午,湯井田,翟戰(zhàn)強,符海芳;空間信息移動服務(wù)現(xiàn)狀及我國發(fā)展對策[J];計算機應(yīng)用研究;2003年09期
5 曾煜;江西移動服務(wù)業(yè)務(wù)技能水平全集團領(lǐng)先[J];通信世界;2003年02期
6 ;挑戰(zhàn)極限 彰顯個性 婁底移動服務(wù)又上新臺階[J];通信企業(yè)管理;2004年11期
7 ;英37家銀行提供移動服務(wù)[J];每周電腦報;2005年39期
8 王琦;;衛(wèi)星移動服務(wù)通過新產(chǎn)品和新業(yè)務(wù)進入主流[J];衛(wèi)星電視與寬帶多媒體;2007年14期
9 華威偉;張e，
本文編號：2466132
本文鏈接：http://sikaile.net/kejilunwen/ruanjiangongchenglunwen/2466132.html
最近更新
教材專著
