【摘要】：隨著在線社交網(wǎng)絡(luò)的快速發(fā)展,微博已被公認(rèn)為是繼電視、郵件、報(bào)紙、廣播等之后的一種新型的網(wǎng)絡(luò)信息傳播方式,兼具著媒體和社交網(wǎng)絡(luò)的特征。隨著微博這個(gè)新型媒體的興起,越來越多的廣告商在這個(gè)社交網(wǎng)絡(luò)平臺(tái)上看到了機(jī)會(huì)。雖然微博這個(gè)社交化網(wǎng)絡(luò)對(duì)于用戶來說僅僅是一個(gè)獲取信息與知識(shí),實(shí)現(xiàn)與好友互動(dòng),展現(xiàn)自我的平臺(tái),但是對(duì)于商家來說,一個(gè)有著那么多注冊(cè)用戶的平臺(tái),它就不僅僅是一個(gè)分享信息的平臺(tái)了,商家可以利用社交平臺(tái)對(duì)其產(chǎn)品和服務(wù)進(jìn)行病毒營(yíng)銷、口碑營(yíng)銷。如今,不管是文本或是富媒體信息,在微博平臺(tái).上均能快速的進(jìn)行傳遞、互通、互動(dòng),由此,越來越多的社交行為從線下轉(zhuǎn)向線上,而這種從線下到線上的轉(zhuǎn)變,不僅僅體現(xiàn)在線下的社交行為上,線下社區(qū)的產(chǎn)品宣傳到線上社區(qū)的產(chǎn)品宣傳的轉(zhuǎn)變尤為明顯。但是如何將線下社區(qū)的廣告宣傳無縫隙移植到線上社區(qū),這是如今廣告商越來越想解決的問題。雖然廣告商可以借助微博社交平臺(tái)采用海投廣告的策略,但這無疑會(huì)造成廣告成本較高,而且會(huì)引起那些對(duì)廣告不感冒的微博用戶的反感,從而將這種反感情緒通過發(fā)布微博迅速傳播到其它微博用戶視線中,進(jìn)而產(chǎn)品的知名度亦會(huì)隨之降低。因?yàn)椴煌膹V告面向不同的用戶群體所屬的虛擬社區(qū),如果能挖掘出每個(gè)用戶所屬的社區(qū)后,根據(jù)微博的局部聚類特性識(shí)別出領(lǐng)域廣告對(duì)應(yīng)的社區(qū),就可提高廣告投放的精準(zhǔn)度。這樣,廣告商不僅可以有針對(duì)性的對(duì)相應(yīng)虛擬社區(qū)的微博用戶投放廣告,而且可以獲得更多投放用戶,從而更能提高廣告的轉(zhuǎn)化率。 本文首先對(duì)與社區(qū)發(fā)現(xiàn)相關(guān)的一些理論技術(shù)進(jìn)行介紹,然后總結(jié)了目前幾類較經(jīng)典的社區(qū)發(fā)現(xiàn)算法,包括基于標(biāo)簽傳播的社區(qū)發(fā)現(xiàn)、以層次為中心的社區(qū)發(fā)現(xiàn)、基于團(tuán)滲透的社區(qū)發(fā)現(xiàn)、基于混合概率模型的社區(qū)發(fā)現(xiàn),并分析了以上幾類社區(qū)發(fā)現(xiàn)算法的適用場(chǎng)景及優(yōu)缺點(diǎn)。在領(lǐng)會(huì)了以上幾類社區(qū)發(fā)現(xiàn)算法之后,本文針對(duì)微博這種相互性網(wǎng)絡(luò)的獨(dú)特性,提出了一種基于RDD (Resilient DistributedDataset)數(shù)據(jù)模型的Spark集群并行計(jì)算思想的多標(biāo)簽傳播社區(qū)發(fā)現(xiàn)算法。本算法借鑒了Raghava等人提出的標(biāo)簽傳播算法LPA的思想,解決了LPA標(biāo)簽傳播算法社區(qū)發(fā)現(xiàn)不穩(wěn)定及準(zhǔn)確度不高的兩大缺陷。為了消除標(biāo)簽傳播算法中不穩(wěn)定的特性,在對(duì)自身社區(qū)標(biāo)簽進(jìn)行更新時(shí),若有多個(gè)可選社區(qū)標(biāo)簽時(shí),不會(huì)任意地對(duì)某一社區(qū)標(biāo)簽進(jìn)行挑選,而是利用一定規(guī)則,將符合這一規(guī)則的社區(qū)標(biāo)簽全部選擇。而為了解決LPA算法準(zhǔn)確率不高的缺點(diǎn),本文引入了微博傳播系數(shù),因?yàn)槲⒉﹤鞑ハ禂?shù)能夠識(shí)別出當(dāng)用戶節(jié)點(diǎn)關(guān)注某一個(gè)人時(shí),該用戶屬于被關(guān)注用戶所在社區(qū)的隸屬程度,不會(huì)平等地對(duì)待每一個(gè)被關(guān)注用戶所屬社區(qū)。另外,本算法也借鑒了Gregory等人提出的COPRA算法,能夠?qū)哂兄丿B的社區(qū)結(jié)構(gòu)進(jìn)行發(fā)現(xiàn),但與其思想也有本質(zhì)的區(qū)別：(1)不會(huì)限制每個(gè)微博用戶所從屬的社區(qū)標(biāo)簽,因?yàn)槲⒉┯脩舻呐d趣愛好是廣泛的,而且是動(dòng)態(tài)變化的；(2)首先根據(jù)用戶所發(fā)微博內(nèi)容挖掘出那些活躍微博用戶所屬社區(qū),然后利用這些已被劃分到相關(guān)社區(qū)的用戶作為已標(biāo)注社區(qū)的節(jié)點(diǎn)進(jìn)行社區(qū)標(biāo)簽傳播。最后,本文將基于RDD(Resilient Distributed Dataset)數(shù)據(jù)模型的Spark集群計(jì)算的消息傳遞機(jī)制的并行計(jì)算思想運(yùn)用于本文提出的算法中,使得算法在處理大規(guī)模圖計(jì)算問題方面成為可能。因此,本文所提出的算法不僅能高效的發(fā)現(xiàn)微博用戶所屬的重疊社區(qū),而且能處理大規(guī)模的圖計(jì)算問題。
[Abstract]:With the rapid development of online social networks, micro-blog has been recognized as a new form of network information communication after TV, mail, newspaper and radio. With the features of media and social networks, more and more advertisers have seen opportunities on this social networking platform with the rise of the new media of micro-blog. But micro-blog is a social network for users to get information and knowledge, to interact with friends, to display their own platform, but for businesses, a platform with so many registered users, it is not only a platform to share information, businesses can use social platforms for their products and services. Virus marketing, word of mouth marketing. Today, both text and rich media information, on the micro-blog platform, can be delivered quickly, interworking, and interactive, and thus more and more social behavior is transferred from the line to line, and the change from the line to the line is not only a reflection of the social behavior under the line, the product of the offline community. The promotion of product publicity to the online community is particularly obvious. But how to transplant advertising campaigns from offline communities to online communities is a problem that advertisers are increasingly trying to solve. Although advertisers can use micro-blog's social platform to adopt a strategy for advertising in the sea, it will undoubtedly lead to higher advertising costs. It causes the disgust of micro-blog users who do not catch a cold, so that this disgust is spread quickly to other micro-blog users through the release of micro-blog, and the popularity of the product will be reduced, as different ads face virtual communities belonging to different user groups, if they can excavate the society of each user. After the area, according to the local clustering characteristics of micro-blog to identify the community corresponding to the field advertising, it can improve the accuracy of advertising. In this way, advertisers can not only put advertising on the micro-blog users in the corresponding virtual community, but also can get more users, which can improve the conversion rate of advertising.
This paper first introduces some theories and techniques related to community discovery, and then summarizes several classical community discovery algorithms, including community discovery based on label propagation, community discovery based on hierarchy, community discovery based on group penetration, community discovery based on mixed probability model, and the analysis of the above categories. The community discovery algorithm is applicable scene and advantages and disadvantages. After understanding the above classes of community discovery algorithms, this paper proposes a multi label propagation community discovery algorithm based on the RDD (Resilient DistributedDataset) data model based on the RDD (Resilient DistributedDataset) data model. This algorithm is used for reference. The idea of label propagation algorithm (LPA) proposed by Raghava and others has solved two major defects in the community found that the LPA tag propagation algorithm is unstable and not highly accurate. In order to eliminate the unstable characteristics of the label propagation algorithm, when the community labels are updated, if there are multiple selectable community labels, it will not be arbitrary to a community. In order to solve the shortcomings of the low accuracy of the LPA algorithm, this article introduces the micro-blog propagation coefficient, because the micro-blog propagation coefficient can recognize that when the user node pays attention to one person, the user belongs to the community where the user is concerned. The degree of membership is not equal to the community of every concerned user. In addition, this algorithm also draws on the COPRA algorithm proposed by Gregory et al. To discover the overlapping community structure, but it is also essentially different from its thought: (1) it will not limit the community labels for each micro-blog user, because micro-blog users The interests are wide and dynamic; (2) first, based on the users' micro-blog content, excavate the community that the active micro-blog users belong to, and then use these users who have been divided into the communities to be tagged as nodes in the community. Finally, this article will be based on RDD (Resilient Distributed Da). Taset) the parallel computing idea of the message transfer mechanism of the Spark cluster calculation in the data model is applied to the algorithm proposed in this paper, which makes it possible to deal with the computation of large scale graphs. Therefore, the proposed algorithm can not only efficiently discover the overlapping communities of micro-blog users, but also deal with large scale graphs. Calculate the problem.
【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】：2014
【分類號(hào)】：TP393.092

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 武志昊;林友芳;Steve Gregory;萬懷宇School of Computer and Information Technology,Beijing Jiaotong University;田盛豐;;Balanced Multi-Label Propagation for Overlapping Community Detection in Social Networks[J];Journal of Computer Science & Technology;2012年03期

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本文編號(hào)：2152712