發(fā)布時(shí)間：2018-08-21 07:42

【摘要】：旅游移動(dòng)服務(wù)是一種情景依賴(lài)度較高的移動(dòng)服務(wù),用戶(hù)在接受旅游產(chǎn)品的個(gè)性化推薦時(shí),當(dāng)前情景對(duì)用戶(hù)偏好會(huì)產(chǎn)生一定程度的影響。關(guān)于旅游移動(dòng)商務(wù)個(gè)性化推薦的研究已成為當(dāng)前熱點(diǎn)之一,目前旅游移動(dòng)商務(wù)個(gè)性化推薦中基于情景的部分研究主要存在缺少維度權(quán)重和推薦結(jié)果類(lèi)似的問(wèn)題。雖然部分研究運(yùn)用了情景要素對(duì)用戶(hù)特征集進(jìn)行擴(kuò)展,卻未充分考慮各情景要素本身對(duì)推薦結(jié)果及用戶(hù)偏好的影響。還有部分研究?jī)H使用時(shí)間、地點(diǎn)等物理環(huán)境維度的情景要素作為構(gòu)建用戶(hù)偏好模型的維度和產(chǎn)生推薦的依據(jù),不同特征的用戶(hù)在同一情景下獲取的推薦結(jié)果相似,并未很好的實(shí)現(xiàn)個(gè)性化推薦。為了提高旅游移動(dòng)商務(wù)的個(gè)性化與適應(yīng)性程度,使用戶(hù)可以通過(guò)旅游移動(dòng)商務(wù)推薦系統(tǒng)更好地進(jìn)行自我服務(wù),本文重點(diǎn)針對(duì)以上兩個(gè)問(wèn)題開(kāi)展了研究。 本文從情景的角度出發(fā),以景點(diǎn)推薦為例,對(duì)旅游移動(dòng)商務(wù)環(huán)境中的個(gè)性化推薦方法展開(kāi)研究,在分析旅游移動(dòng)商務(wù)和個(gè)性化推薦方法研究現(xiàn)狀的基礎(chǔ)上,綜合使用情景理論、個(gè)性化推薦方法,在當(dāng)前情景、歷史情景、用戶(hù)歷史行為記錄和用戶(hù)基本特征四個(gè)維度應(yīng)用貝葉斯網(wǎng)絡(luò)對(duì)用戶(hù)偏好進(jìn)行推理,構(gòu)建了多維用戶(hù)偏好模型。在此基礎(chǔ)上,本文對(duì)已有個(gè)性化推薦方法進(jìn)行了改進(jìn),通過(guò)實(shí)驗(yàn)驗(yàn)證證明了本文提出的旅游移動(dòng)商務(wù)環(huán)境中的基于多維用戶(hù)偏好模型的個(gè)性化推薦方法的推薦質(zhì)量在一定程度上優(yōu)于傳統(tǒng)的個(gè)性化推薦算法。
[Abstract]:Tourism mobile service is a highly dependent mobile service. When users accept personalized recommendation of tourism products, the current situation will have a certain degree of impact on user preferences. The research on personalized recommendation of tourism mobile commerce has become one of the current hot spots. At present, there is a lack of dimensionality weight and similar recommendation results in the research of situation-based personalized recommendation of tourism mobile commerce. Although some of the studies use situational elements to extend the user feature set, they do not fully consider the impact of each situational element itself on the recommended results and user preferences. Some studies only use the scene elements of physical environment dimension such as time and place as the dimension of constructing user preference model and the basis of producing recommendation. The results obtained by users with different characteristics in the same situation are similar. Not very well to achieve personalized recommendation. In order to improve the degree of personalization and adaptability of tourism mobile commerce, and make users can better self-service through tourism mobile commerce recommendation system, this paper focuses on the above two problems. From the perspective of scene, this paper takes the recommendation of scenic spots as an example to study the personalized recommendation method in the tourism mobile commerce environment. On the basis of analyzing the present situation of the research on the tourism mobile commerce and the personalized recommendation method, this paper synthetically uses the scenario theory. In the four dimensions of current situation, historical situation, user history behavior record and user basic characteristics, Bayesian network is used to infer user preference, and a multi-dimensional user preference model is constructed. On this basis, the existing personalized recommendation methods have been improved. The experimental results show that the proposed personalized recommendation method based on multi-dimensional user preference model is superior to the traditional personalized recommendation algorithm to some extent.
【學(xué)位授予單位】：華東理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類(lèi)號(hào)】：F274;F713.36;F590

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本文編號(hào)：2195022