本文選題：微博系統(tǒng) + 朋友推薦　； 參考：《計算機工程與應用》2017年13期

【摘要】：近年來,微博的蓬勃發(fā)展吸引了大量網(wǎng)絡用戶,用戶所發(fā)海量微博呈現(xiàn)的大數(shù)據(jù)環(huán)境成為理解用戶行為的重要資源。目前,大量在線朋友推薦研究通過對微博內容分析推斷用戶的興趣和喜好以進行朋友推薦,但大多數(shù)已有研究忽略了用戶位置和興趣之間的潛在關系。事實上,多數(shù)情況下用戶真正感興趣的還是他周圍的人。為此,提出了基于地理近鄰關系的朋友推薦方法,通過把所處位置周圍興趣愛好相似的微博用戶彼此推薦,為用戶提供了與周圍可能感興趣的人聯(lián)系的獨特渠道。仿真分析證明,與傳統(tǒng)朋友推薦方法相比,基于地理近鄰的朋友推薦具有較高的推薦性能。
[Abstract]:In recent years, the vigorous development of Weibo has attracted a large number of network users. The big data environment presented by massive Weibo issued by users has become an important resource to understand user behavior. At present, a large number of online friend recommendation studies infer the interests and preferences of users by analyzing the content of Weibo, but most of the previous studies have neglected the potential relationship between user location and interest. In fact, in most cases the user is really interested in the people around him. In this paper, a method of recommending friends based on geographical nearest neighbor relationship is proposed. By recommending Weibo users with similar interests and hobbies around their location, it provides a unique channel for users to communicate with people who may be interested in their surroundings. The simulation results show that compared with the traditional friend recommendation method, the friend recommendation based on geographical nearest neighbor has higher recommendation performance.
【作者單位】： 天津師范大學計算機與信息工程學院;電子科技大學計算機與工程學院;
【基金】：國家自然科學基金(No.61103227,No.61272526,No.61472068,No.61572113) 中國博士后基金(No.2014M550466,No.2014M562308,No.2014M562310)
【分類號】：TP391.3;TP393.092
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本文編號：2057335