【摘要】：【目的/意義】移動(dòng)互聯(lián)網(wǎng)時(shí)代,移動(dòng)電子商務(wù)用戶的個(gè)性化信息需求具有極強(qiáng)的情景依賴性與感知信任性,針對目前移動(dòng)商務(wù)信息服務(wù)個(gè)性化和準(zhǔn)確性較低,提出融入用戶個(gè)性化情景與用戶間信任關(guān)系的推薦模型�！痉椒�/過程】首先,通過用戶當(dāng)前情景和歷史評分?jǐn)?shù)據(jù)計(jì)算出對每個(gè)用戶即時(shí)信息需求影響最大的K個(gè)情景要素,以此構(gòu)造用戶個(gè)性化情景,然后結(jié)合不同信任環(huán)境下的用戶信任度矩陣改進(jìn)已有的不同信任信息環(huán)境下用戶情景興趣推薦方法,進(jìn)而進(jìn)行項(xiàng)目推薦�！窘Y(jié)果/結(jié)論】通過Movie lens與Book-Crossing數(shù)據(jù)集對本文提出的算法和其它兩種算法進(jìn)行比較,實(shí)驗(yàn)結(jié)果表明:本模型具有較高的推薦準(zhǔn)確率,可有效地解決移動(dòng)商務(wù)環(huán)境下的個(gè)性化推薦問題。
[Abstract]:[Objective/Significance] In the era of mobile Internet, the personalized information needs of mobile e-commerce users have strong situational dependence and perceptual trust. Aiming at the low individuation and accuracy of mobile commerce information services, a recommendation model incorporating user personalized scenarios and trust relationship between users is proposed. Firstly, K scenario elements which have the greatest impact on each user's instant information demand are calculated by user's current scenario and historical score data, so as to construct user's personalized scenario. Then, the user's scenario interest recommendation method under different trust information environments is improved by combining the user's trust matrix under different trust environments, and then the user's scenario interest recommendation method under different trust information environments [Results/Conclusion] Comparing Movie lens and Book-Crossing datasets, the proposed algorithm and the other two algorithms show that the model has high recommendation accuracy and can effectively solve the personalized recommendation problem in mobile commerce environment.
【作者單位】： 哈爾濱理工大學(xué)管理學(xué)院;哈爾濱理工大學(xué)高新技術(shù)產(chǎn)業(yè)發(fā)展研究中心;
【基金】：國家自然科學(xué)基金(71272191);國家自然科學(xué)基金(71672050) 黑龍江省自然科學(xué)基金項(xiàng)目(G201301)
【分類號】：F713.36;G252

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