本文選題：移動商務　切入點：位置　出處：《海南大學》2016年碩士論文

【摘要】：隨著移動互聯(lián)網(wǎng)的普及,人民生活進一步的“互聯(lián)網(wǎng)化”。為了滿足用戶隨時隨地的移動需求,特別是在移動醫(yī)療、移動金融等新興領域,移動應用程序需要在同一時間多個維度向用戶提供服務。在互聯(lián)網(wǎng)中移動互聯(lián)網(wǎng)業(yè)務大致可分為：手機在線支付、網(wǎng)上購物、網(wǎng)上銀行和旅游預訂等移動應用,它們同比增長率都在40%以上。其中移動互聯(lián)網(wǎng)用戶是主要推動力,這為移動商務的進一步發(fā)展提供了良好的基礎。與傳統(tǒng)的電子商務相比較而言,移動商務的服務對象具有高度的服務性和流動性。因此,為了適應移動商務的新特性,必須在滿足用戶購買需求的基礎上,對用戶進行服務定制。針對這一現(xiàn)狀,本文對移動商務下的服務推薦系統(tǒng)進行了深入的研究。本文的主要工作如下：第一,闡述了在移動商務環(huán)境下開展服務推薦的意義,從推薦算法動態(tài)適應用戶興趣變化的角度總結了國內(nèi)外研究現(xiàn)狀。同時根據(jù)移動商務用戶特點,從位置和瀏覽路徑兩方面對移動商務下的服務推薦算法進行深入分析。第二,利用移動商務環(huán)境下,系統(tǒng)可以實時獲取用戶地理位置的優(yōu)勢,在傳統(tǒng)推薦算法的基礎上引入距離變量。根據(jù)用戶瀏覽商品的不同,實時調(diào)整距離變量,進而向用戶推薦最合適的商品。該方法解決了由于外部信息改變帶來的用戶短期興趣變化的問題。第三,在引入位置解決用戶短期興趣的基礎上,考慮到移動商務環(huán)境下,用戶數(shù)據(jù)集的稀疏性、冷啟動問題,采用蟻群算法依據(jù)用戶的瀏覽路徑,提高算法的推薦精度。最后,通過仿真實驗,驗證在移動商務下引入距離變量和蟻群算法的可行性。實驗表明,引入距離變量以后推薦系統(tǒng)可以根據(jù)用戶具體的距離敏感度來為用戶提供更加適合當前環(huán)境的服務推薦,基于蟻群的用戶瀏覽路徑算法可以有效的提高推薦的精度。
[Abstract]:With the popularity of the mobile Internet, people's life further "Internet."In order to meet the mobile needs of users, especially in the emerging areas of mobile medicine, mobile finance and so on, mobile applications need to provide services to users in multiple dimensions at the same time.Mobile Internet services in the Internet can be broadly divided into mobile applications such as mobile online payment, online shopping, online banking and travel booking, all of which are growing at more than 40 percent year-on-year.Mobile Internet users are the main driving force, which provides a good basis for the further development of mobile commerce.Compared with the traditional e-commerce, mobile commerce has a high degree of service and mobility.Therefore, in order to adapt to the new features of mobile commerce, it is necessary to customize the service to users on the basis of meeting the purchase needs of users.In view of this present situation, this paper carries on the thorough research to the service recommendation system under the mobile commerce.The main work of this paper is as follows: first, the significance of service recommendation in the mobile commerce environment is expounded, and the research status at home and abroad is summarized from the point of view of dynamic adaptation of recommendation algorithm to the change of user interest.At the same time, according to the characteristics of mobile commerce users, the service recommendation algorithm under mobile commerce is analyzed from two aspects: location and browsing path.Secondly, under the mobile commerce environment, the system can obtain the advantage of users' geographical location in real time, and introduce the distance variable on the basis of the traditional recommendation algorithm.The distance variable is adjusted in real time to recommend the most suitable item according to the different items viewed by the user.This method solves the problem of the change of user's short-term interest caused by the change of external information.Thirdly, on the basis of introducing location to solve the short-term interests of users, considering the sparse and cold start problem of user data set in the mobile commerce environment, ant colony algorithm is used to improve the recommendation accuracy of the algorithm according to the browsing path of users.Finally, the feasibility of introducing distance variables and ant colony algorithm in mobile commerce is verified by simulation experiments.The experimental results show that the recommendation system can provide users with more suitable service recommendation for the current environment according to the specific distance sensitivity after the introduction of distance variables. The user browsing path algorithm based on ant colony can effectively improve the accuracy of recommendation.
【學位授予單位】：海南大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TP391.3;TP18

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本文編號：1710093