本文關(guān)鍵詞： 移動(dòng)通信下 社交網(wǎng)絡(luò) 服務(wù)提取　出處：《計(jì)算機(jī)仿真》2016年12期 　論文類型：期刊論文

【摘要】：對(duì)移動(dòng)通信中網(wǎng)絡(luò)個(gè)性化服務(wù)信息進(jìn)行準(zhǔn)確提取,可提高移動(dòng)通信信息服務(wù)的質(zhì)量。進(jìn)行網(wǎng)絡(luò)個(gè)性化服務(wù)信息提取時(shí),需要預(yù)測(cè)用戶對(duì)服務(wù)項(xiàng)目的未知評(píng)分,并計(jì)算用戶的時(shí)間行為信息獲得網(wǎng)絡(luò)用戶興趣相似度,完成網(wǎng)絡(luò)個(gè)性化服務(wù)信息提取。但是傳統(tǒng)方法通過(guò)入挖掘潛在的網(wǎng)絡(luò)用戶社會(huì)關(guān)系,對(duì)移動(dòng)通信中網(wǎng)絡(luò)個(gè)性化服務(wù)信息進(jìn)行提取,不能精確計(jì)算網(wǎng)絡(luò)用戶興趣相似度,存在信息提取不準(zhǔn)確、效率低的問(wèn)題。提出一種關(guān)于用戶興趣度的移動(dòng)通信中網(wǎng)絡(luò)個(gè)性化服務(wù)信息提取方法。上述方法首先將移動(dòng)通信過(guò)程中社交網(wǎng)絡(luò)與用戶評(píng)分矩陣組成一個(gè)矩陣,融合隨機(jī)梯度下降理論對(duì)該矩陣進(jìn)行分解,預(yù)測(cè)用戶對(duì)服務(wù)項(xiàng)目的未知評(píng)分,獲取相似用戶對(duì)同一服務(wù)項(xiàng)目興趣度的預(yù)測(cè)值與真實(shí)值之間的誤差,并將用戶訪問(wèn)時(shí)間引入社交網(wǎng)絡(luò)服務(wù)提取過(guò)程中,采用用戶的時(shí)間行為信息獲得網(wǎng)絡(luò)用戶興趣相似度,計(jì)算社交網(wǎng)絡(luò)用戶近似度和時(shí)間衰弱項(xiàng),依據(jù)計(jì)算的結(jié)果對(duì)網(wǎng)絡(luò)個(gè)性化服務(wù)信息進(jìn)行提取。仿真結(jié)果表明,所提方法可以有效提高移動(dòng)通信中網(wǎng)絡(luò)個(gè)性化服務(wù)信息提取精度,網(wǎng)絡(luò)開銷比較穩(wěn)定。
[Abstract]:The personalized service information in mobile communication are extracted accurately, can improve the quality of mobile communication and information services. Extraction of personalized service of network information, the user needs to predict the unknown on the service item score, access to the network users interest similarity time behavior information and calculate the user's complete extraction of personalized service information network. But the traditional method by the mining potential network users of social relations, the personalized service information in mobile communication network are extracted, user interest similarity cannot be calculated accurately, the existence of information extraction is not accurate, the problem of low efficiency. This paper proposed a method of personalized service of network information on mobile communication user interest degree. The first social network and users mobile communication in the process of scoring matrix composed of a matrix of stochastic gradient descent on the fusion theory Matrix decomposition, prediction of the unknown user service score, similar to the same user access prediction service project interest value and the error between the true value, and the user access time into social network service extraction process, access to the network users interest similarity using the time information of user behavior, calculate the approximate degree and time. Social network users, personalized service of Web information extraction according to the calculation results. The simulation results show that the proposed method can effectively improve the extraction accuracy of personalized service of network information in mobile communication network, the overhead is relatively stable.

【作者單位】： 長(zhǎng)沙理工大學(xué)計(jì)算機(jī)與通信工程學(xué)院;
【基金】：湖南省科學(xué)技術(shù)計(jì)劃項(xiàng)目(2011FJ3086)
【分類號(hào)】：TN929.5
【正文快照】： _ 1 51胃 近年來(lái),隨著現(xiàn)代科學(xué)計(jì)算機(jī)技術(shù)的迅猛發(fā)展,互聯(lián)網(wǎng)規(guī)模的不斷擴(kuò)大,以及移動(dòng)終端的廣泛普及,諸如Facebook、Twitter、Tumblr等社交網(wǎng)絡(luò)已逐漸成為人們生活中必不可少 的一部分[1_2]。人們享受著移動(dòng)社交網(wǎng)絡(luò)為廣大用戶提供的信息傳播形式服務(wù)[3]。然而信息的迅速傳播

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