本文選題：時空交互 + 社交關(guān)系��； 參考：《中國礦業(yè)大學(xué)》2017年碩士論文

【摘要】：社交平臺與位置技術(shù)的緊密結(jié)合,促進(jìn)了基于位置的社交網(wǎng)絡(luò)的形成和發(fā)展。集成了GPS、無線網(wǎng)絡(luò)、衛(wèi)星定位等定位功能的智能設(shè)備為用戶在社交平臺上的位置標(biāo)記、位置簽到和位置共享提供了極大的便利。由此,產(chǎn)生了海量的、帶有用戶位置的數(shù)據(jù)。這些數(shù)據(jù)蘊含著大量的信息,能夠為基于位置服務(wù)(如:用戶社交關(guān)系發(fā)現(xiàn)、智能交通、旅游推薦、犯罪活動路徑追蹤等)的相關(guān)應(yīng)用提供數(shù)據(jù)支持,迫切地需要研究人員對其進(jìn)行全面的分析和有效的計算。本課題以基于位置的社交網(wǎng)絡(luò)數(shù)據(jù)為研究對象,以用戶社交關(guān)系強度計算和用戶社交關(guān)系動態(tài)變化特征提取為研究目標(biāo),研究了靈活、全面的用戶社交關(guān)系挖掘相關(guān)的理論和方法。本課題的主要研究工作如下:(1)本課題深入分析位置社交網(wǎng)絡(luò)的時空交互性,充分考慮用戶的行為特征和時空交互信息,提出了基于時空交互的用戶社交關(guān)系強度計算方法。該方法通過對用戶的時空交互情境進(jìn)行建模,調(diào)整用戶在不同情境下的交互權(quán)重,能夠更加精確地計算用戶之間的社交關(guān)系強度,更全面地發(fā)現(xiàn)用戶之間的社交關(guān)系。(2)本課題深入分析位置社交網(wǎng)絡(luò)中用戶之間時空交互行為的變化特性,充分考慮用戶行為特征和時空交互信息的變化情況,提出了基于用戶行為特征漂移的動態(tài)社交關(guān)系強度計算方法。該方法通過構(gòu)建用戶行為特征漂移模型,利用時間切片技術(shù),對用戶之間的動態(tài)社交關(guān)系強度進(jìn)行精確、全面和實時地量化計算,并提取用戶社交關(guān)系的動態(tài)變化特征,有效地緩解了基于位置的社交網(wǎng)絡(luò)數(shù)據(jù)的稀疏性問題。(3)本課題為了對基于位置的社交網(wǎng)絡(luò)數(shù)據(jù)展開深入研究,擴(kuò)充和豐富用戶社交關(guān)系挖掘領(lǐng)域的相關(guān)理論和方法,加強用戶社交關(guān)系挖掘理論和實踐的結(jié)合,以基于時空交互的用戶社交關(guān)系強度計算和基于用戶行為特征漂移動態(tài)社交關(guān)系強度計算等研究成果為基礎(chǔ),設(shè)計并實現(xiàn)了時空社交關(guān)系計算原型系統(tǒng)。
[Abstract]:The close combination of social platform and location technology promotes the formation and development of location-based social network. Intelligent devices that integrate GPS, wireless network, satellite positioning and other location functions provide users with great convenience for location marking, location check-in and location sharing on social platforms. As a result, massive amounts of data with user locations are generated. The data contains a large amount of information that can support applications based on location-based services (such as user social relationship discovery, intelligent transportation, travel recommendations, criminal activity path tracking, etc.). There is an urgent need for comprehensive analysis and effective calculation by researchers. Based on the location-based social network data, the research object of this paper is to calculate the strength of user social relationship and extract the dynamic change feature of user social relationship. Comprehensive user social relationship mining related theories and methods. The main research work of this paper is as follows: (1) this paper deeply analyzes the spatio-temporal interaction of locational social networks, fully considers the behavior characteristics of users and space-time interactive information, and puts forward a method to calculate the intensity of user social relations based on spatio-temporal interaction. By modeling the user's space-time interactive situation and adjusting the user's interaction weight in different situations, the method can calculate the intensity of social relationship between users more accurately. Find out the social relationship between users in a more comprehensive way.) in this paper, we deeply analyze the changing characteristics of spatio-temporal interaction behavior among users in social networks, and fully consider the changes of user behavior characteristics and spatio-temporal interactive information. A dynamic social relationship strength calculation method based on user behavior drift is proposed. By constructing user behavior drift model and using time slice technology, the dynamic social relationship intensity between users is calculated accurately, comprehensively and in real time, and the dynamic change feature of user social relationship is extracted. In order to deeply study the location-based social network data, expand and enrich the relevant theories and methods in the field of user social relationship mining, which effectively alleviates the sparse problem of location-based social network data. To strengthen the combination of theory and practice of user social relationship mining, based on the research results of user social relationship strength calculation based on space-time interaction and dynamic social relationship strength calculation based on user behavior characteristic drift. A prototype system of spatiotemporal social relationship computing is designed and implemented.
【學(xué)位授予單位】：中國礦業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP393.09

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