本文選題：移動(dòng)商務(wù)　切入點(diǎn)：位置　出處：《海南大學(xué)》2016年碩士論文

【摘要】：隨著移動(dòng)互聯(lián)網(wǎng)的普及,人民生活進(jìn)一步的“互聯(lián)網(wǎng)化”。為了滿足用戶隨時(shí)隨地的移動(dòng)需求,特別是在移動(dòng)醫(yī)療、移動(dòng)金融等新興領(lǐng)域,移動(dòng)應(yīng)用程序需要在同一時(shí)間多個(gè)維度向用戶提供服務(wù)。在互聯(lián)網(wǎng)中移動(dòng)互聯(lián)網(wǎng)業(yè)務(wù)大致可分為：手機(jī)在線支付、網(wǎng)上購物、網(wǎng)上銀行和旅游預(yù)訂等移動(dòng)應(yīng)用,它們同比增長率都在40%以上。其中移動(dòng)互聯(lián)網(wǎng)用戶是主要推動(dòng)力,這為移動(dòng)商務(wù)的進(jìn)一步發(fā)展提供了良好的基礎(chǔ)。與傳統(tǒng)的電子商務(wù)相比較而言,移動(dòng)商務(wù)的服務(wù)對(duì)象具有高度的服務(wù)性和流動(dòng)性。因此,為了適應(yīng)移動(dòng)商務(wù)的新特性,必須在滿足用戶購買需求的基礎(chǔ)上,對(duì)用戶進(jìn)行服務(wù)定制。針對(duì)這一現(xiàn)狀,本文對(duì)移動(dòng)商務(wù)下的服務(wù)推薦系統(tǒng)進(jìn)行了深入的研究。本文的主要工作如下：第一,闡述了在移動(dòng)商務(wù)環(huán)境下開展服務(wù)推薦的意義,從推薦算法動(dòng)態(tài)適應(yīng)用戶興趣變化的角度總結(jié)了國內(nèi)外研究現(xiàn)狀。同時(shí)根據(jù)移動(dòng)商務(wù)用戶特點(diǎn),從位置和瀏覽路徑兩方面對(duì)移動(dòng)商務(wù)下的服務(wù)推薦算法進(jìn)行深入分析。第二,利用移動(dòng)商務(wù)環(huán)境下,系統(tǒng)可以實(shí)時(shí)獲取用戶地理位置的優(yōu)勢,在傳統(tǒng)推薦算法的基礎(chǔ)上引入距離變量。根據(jù)用戶瀏覽商品的不同,實(shí)時(shí)調(diào)整距離變量,進(jìn)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(chǔ)上,考慮到移動(dòng)商務(wù)環(huán)境下,用戶數(shù)據(jù)集的稀疏性、冷啟動(dòng)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(shí)驗(yàn),驗(yàn)證在移動(dòng)商務(wù)下引入距離變量和蟻群算法的可行性。實(shí)驗(yàn)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(dāng)前環(huán)境的服務(wù)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(xué)位授予單位】：海南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.3;TP18

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