本文關(guān)鍵詞： 社會(huì)化網(wǎng)絡(luò) 用戶(hù)關(guān)系強(qiáng)度 活動(dòng)領(lǐng)域分類(lèi) 直接關(guān)系 間接關(guān)系　出處：《浙江工商大學(xué)》2017年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：隨著互聯(lián)網(wǎng)的發(fā)展,社會(huì)化網(wǎng)絡(luò)迅速流行,并在人們的日常生活中發(fā)揮著至關(guān)重要的作用,為信息傳播、經(jīng)驗(yàn)分享、生活交流等活動(dòng)開(kāi)拓了重要渠道。也因此,社會(huì)化網(wǎng)絡(luò)中用戶(hù)間的關(guān)系強(qiáng)度引起了研究者的高度重視。社會(huì)化網(wǎng)絡(luò)在多個(gè)領(lǐng)域的重要作用逐漸凸顯,如應(yīng)用于好友推薦、商品推薦、鏈路預(yù)測(cè)等。就個(gè)性化服務(wù)推薦而言,社會(huì)化網(wǎng)絡(luò)用戶(hù)間的關(guān)系強(qiáng)度是進(jìn)行推薦的重要依據(jù)。目標(biāo)推薦用戶(hù)的喜好往往跟與他有較強(qiáng)關(guān)系強(qiáng)度的用戶(hù)更接近,而來(lái)自具有親密關(guān)系的人的推薦也往往是更容易被接受的。因此,社會(huì)化網(wǎng)絡(luò)中用戶(hù)間關(guān)系強(qiáng)度的重要性不言而喻。但目前已有的關(guān)系強(qiáng)度計(jì)算方法考慮都較為片面,許多研究只是籠統(tǒng)地對(duì)社會(huì)化網(wǎng)絡(luò)中用戶(hù)間的關(guān)系強(qiáng)度進(jìn)行計(jì)算,而未針對(duì)特定的情況進(jìn)行研究,并且許多研究只針對(duì)社會(huì)化網(wǎng)絡(luò)中用戶(hù)間存在的直接關(guān)系進(jìn)行研究,而忽略具有舉足輕重的間接關(guān)系,因此計(jì)算結(jié)果的精確度有待提高�；谝陨蠁�(wèn)題,本文提出了一種基于活動(dòng)領(lǐng)域分類(lèi)與間接關(guān)系融合的社會(huì)化網(wǎng)絡(luò)用戶(hù)關(guān)系強(qiáng)度計(jì)算模型,主要研究?jī)?nèi)容主要包括以下幾個(gè)方面:第一,通過(guò)爬蟲(chóng)獲取社會(huì)化網(wǎng)絡(luò)中的相關(guān)數(shù)據(jù),對(duì)數(shù)據(jù)進(jìn)行預(yù)處理(包括中文分詞、去停用詞),轉(zhuǎn)化為相應(yīng)的文檔數(shù)據(jù)集,去除垃圾數(shù)據(jù),有助于計(jì)算結(jié)果準(zhǔn)確性的提高。第二,對(duì)社會(huì)化網(wǎng)絡(luò)中用戶(hù)群的交互活動(dòng)進(jìn)行活動(dòng)領(lǐng)域分類(lèi)。用LDA算法對(duì)用戶(hù)交互活動(dòng)文檔進(jìn)行集群,利用標(biāo)準(zhǔn)化谷歌距離將結(jié)果集群與活動(dòng)領(lǐng)域名稱(chēng)(工作、飲食、購(gòu)物、旅游、運(yùn)動(dòng)、娛樂(lè))進(jìn)行相關(guān)度計(jì)算,確定每個(gè)結(jié)果集群所屬的活動(dòng)領(lǐng)域。之后再進(jìn)一步通過(guò)相關(guān)度的計(jì)算判斷每個(gè)交互活動(dòng)文檔所屬的活動(dòng)領(lǐng)域。結(jié)合活動(dòng)領(lǐng)域分類(lèi)對(duì)社會(huì)化網(wǎng)絡(luò)中用戶(hù)間的關(guān)系強(qiáng)度進(jìn)行計(jì)算有助于該研究成果后續(xù)能更有針對(duì)性地應(yīng)用于其他領(lǐng)域,如應(yīng)用于個(gè)性化推薦時(shí),可以分領(lǐng)域進(jìn)行推薦,提高推薦的成功率。第三,直接關(guān)系強(qiáng)度計(jì)算中充分考慮多種影響因素。結(jié)合個(gè)體相似性、時(shí)間性、互動(dòng)性對(duì)每個(gè)交互活動(dòng)領(lǐng)域內(nèi)用戶(hù)間的直接關(guān)系強(qiáng)度進(jìn)行計(jì)算,充分考慮了多方面的關(guān)系強(qiáng)度影響因素,有利于直接關(guān)系強(qiáng)度的準(zhǔn)確計(jì)算。第四,融合間接關(guān)系于關(guān)系強(qiáng)度計(jì)算過(guò)程中�？紤]到間接關(guān)系在社會(huì)化網(wǎng)絡(luò)關(guān)系網(wǎng)中具有舉足輕重的地位,在最終關(guān)系強(qiáng)度的計(jì)算中融合了間接關(guān)系,不僅解決了不存在直接關(guān)系而只存在間接關(guān)系的用戶(hù)間關(guān)系強(qiáng)度無(wú)法計(jì)算的問(wèn)題,而且提高了關(guān)系強(qiáng)度計(jì)算的準(zhǔn)確性。第五,提出了衡量關(guān)系強(qiáng)度計(jì)算結(jié)果準(zhǔn)確性的評(píng)價(jià)指標(biāo)。分別與基于文檔級(jí)別、集群級(jí)別、微博會(huì)話的活動(dòng)領(lǐng)域分類(lèi)方法比較,評(píng)價(jià)本文所提出的活動(dòng)領(lǐng)域分類(lèi)方法的效率。并根據(jù)準(zhǔn)確率、召回率和標(biāo)準(zhǔn)衡量搜索引擎質(zhì)量指標(biāo)(NDCG)作為實(shí)驗(yàn)結(jié)果的評(píng)價(jià)指標(biāo),將本文所提出的關(guān)系強(qiáng)度計(jì)算方法分別與線性組合方法、通用框架模型方法比較,實(shí)驗(yàn)結(jié)果表明本文所提的基于活動(dòng)領(lǐng)域分類(lèi)與間接關(guān)系融合的社會(huì)化網(wǎng)絡(luò)用戶(hù)關(guān)系強(qiáng)度計(jì)算方法更優(yōu)。
[Abstract]:With the development of the Internet, the rapid popular social network, and in people's daily life plays a vital role in sharing the experience for the dissemination of information, communication and other activities, life opens up an important channel. Therefore, the strength of relationship between users in social network have attracted the attention of researchers in social networking. An important role in many fields gradually highlighted, as for friend recommendation, recommendation, link prediction. The personalized service recommendation, the strength of the relationship between social network users is an important basis for the recommended target. Recommended user preferences tend to have strong relationship with his strength and is closer to the user. From people with intimate relations recommended also tend to be more easily accepted. Therefore, it is self-evident importance of relationship strength between users in social network. But the existing intensity meter Considering the calculation method are relatively one-sided, many studies only loosely on social relationship strength between users in the network are calculated, but not for the specific case study, and many studies are focused on the direct relationship between social network among users of neglect has indirect relationship important, therefore the calculation results the accuracy needs to be improved. Based on the above problems, this paper presents a computational model of social network user relationship strength fusion classification based on field of activity and the indirect relation, the main research contents include the following aspects: first, access to relevant data in social network by crawler, data preprocessing (including Chinese segmentation, go to stop words), into the corresponding document data set, remove garbage data, help to improve the accuracy of the calculation results. Second, on the social network Interactive activities in the user group of activities in the field of classification. Cluster of user interaction activities document with the LDA algorithm, using standard Google distance name cluster and field results (work, food, shopping, travel, sports, entertainment) related calculation, determine the result of each cluster belongs to the field of activity. Further through calculation of the correlation judgment of each document are interactive activities activities. Combining activities in the field of classification of relationship strength between users in the network of social computing is helpful for the subsequent research results can be more targeted application in other fields, such as for personalized recommendation, can be divided into the field of recommendation and recommended to improve success rate. Third, a variety of factors considered in the calculation of direct relationship strength. Combined with the individual similarity, timeliness, interaction of each interaction in the field of use Calculate direct relationship strength between households, fully considering the factors of relationship strength to many factors, there are conducive to the accurate calculation of direct relationship strength. In fourth, the indirect relationship between fusion relationship strength calculation process. Considering the indirect relationship plays an important role in the social relationship network, in the calculation of the final strength of the relationship fusion of indirect relationship, not only solved there is no direct relationship between strength can not be calculated only indirect relation between users, but also improve the accuracy of relationship strength calculation. Fifth, put forward the measure of relationship strength calculation accuracy evaluation index. And based on the document level, cluster level, micro-blog session activities the field classification method, efficiency evaluation of this field of activity. According to the classification accuracy rate, recall rate and standard search engine The quality index (NDCG) was used as the index to evaluate the experimental results, the method with linear combination method of strength calculation of the relationship will be presented in this paper, the comparative method of general framework model, the experimental results show that the social network user relationship strength fusion classification based on field of activity and the indirect relationship between the proposed calculation method is better.

【學(xué)位授予單位】：浙江工商大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP393.09

【參考文獻(xiàn)】

相關(guān)期刊論文 前6條

1 琚春華;陶婉瓊;許厘，

本文編號(hào)：1506894