本文選題：多源數(shù)據(jù)融合 + 感知數(shù)據(jù)��； 參考：《西北工業(yè)大學(xué)》2016年博士論文

【摘要】：網(wǎng)絡(luò)技術(shù)的誕生將人類在物理空間的交互拓展延伸到了虛擬的信息空間中,克服了空間對于人類的制約作用,大大縮短了信息傳播時間,強(qiáng)化了用戶之間的交互。隨著感知技術(shù)的進(jìn)一步發(fā)展和移動計算終端的出現(xiàn),人類活動在兩個空間中不斷地交替切換,從而使得物理空間和信息空間的互動更加頻繁,并在兩個空間中留下了大量的數(shù)字信息。多個空間的交融促進(jìn)了Cyber-Physical-Social System(CPSS)的出現(xiàn)。CPSS的多源數(shù)據(jù)空間具有異構(gòu)性、動態(tài)性、稀疏性和高噪聲等特性,其對數(shù)據(jù)表示、處理和分析等提出了諸多挑戰(zhàn)。本文以健康數(shù)據(jù)分析為應(yīng)用背景,研究了從物理空間中的感知數(shù)據(jù)和信息空間中的在線數(shù)據(jù)中抽取與健康相關(guān)的語義信息方法。本文主要研究工作與創(chuàng)新如下:多源數(shù)據(jù)及其計算模型多源數(shù)據(jù)空間包含多種多樣的數(shù)據(jù)信息,這些數(shù)據(jù)具有異構(gòu)性、動態(tài)性、稀疏性、高噪聲等特點(diǎn)。本文分析了感知數(shù)據(jù)和在線數(shù)據(jù)的特點(diǎn),分別定義了感知數(shù)據(jù)模型和在線數(shù)據(jù)模型,實(shí)現(xiàn)不同特質(zhì)數(shù)據(jù)的表示和存儲。為了實(shí)現(xiàn)不同類型數(shù)據(jù)的混合計算,本文采用本體表示模型抽象不同數(shù)據(jù)之間的關(guān)系,并基于知識推理構(gòu)建相應(yīng)的計算模型。輕量級的感知數(shù)據(jù)健康語義分析隨著大量生理感知器件的使用,利用感知設(shè)備對用戶健康狀態(tài)進(jìn)行檢測和分析成為可能。本文重點(diǎn)研究了基于移動設(shè)備監(jiān)控用戶運(yùn)動水平的方法。首先,本文對用戶行為識別研究從感知技術(shù)和識別算法的角度進(jìn)行了綜述性的分析。重點(diǎn)研究輕量級的行為分析方法,以達(dá)到長期監(jiān)控運(yùn)動狀態(tài)的目的。本文從采樣頻率、特征選擇和算法角度入手,針對移動終端資源受限的特點(diǎn),提出了一個輕量級層次化的行為分析算法,其通過降低采樣頻率和頻域數(shù)據(jù)的使用概率,實(shí)現(xiàn)識別正確率和能耗之間的平衡�；谠撔袨榉治鏊惴�,本文使用代謝當(dāng)量分析方法實(shí)現(xiàn)用戶的運(yùn)動狀態(tài)評估�；谠~向量的在線數(shù)據(jù)健康語義分析用戶在線活動是人類物理交互在網(wǎng)絡(luò)空間的延伸,其中可能隱含用戶的健康信息。本文研究了從大量的在線數(shù)據(jù)尤其是文本數(shù)據(jù)中挖掘用戶健康行為的方法。首先研究了在線數(shù)據(jù)采集的策略和方法,構(gòu)建了一個社交媒體數(shù)據(jù)采集平臺,實(shí)現(xiàn)從不同的社交服務(wù)平臺采集數(shù)據(jù)信息。然后,從交互特征、語義特征和拓?fù)涮卣鞯冉嵌确治隽嗽诰�數(shù)據(jù)與用戶健康行為屬性之間的關(guān)系。最后借助詞向量的文本表示技術(shù),以控?zé)煘閼?yīng)用背景,提出了由在線數(shù)據(jù)判斷用戶是否為煙草產(chǎn)品使用者的算法。層次化的多源健康數(shù)據(jù)融合方法針對感知數(shù)據(jù)和在線數(shù)據(jù)的差異,本文研究了CPSS系統(tǒng)中的多源數(shù)據(jù)融合問題,從特征級融合和決策級融合兩個層次分析了多源數(shù)據(jù)融合方法。針對決策級融合,本文采用知識推理方法抽取高級語義信息;針對特征融合,本文基于多源特征提出了一個社群發(fā)現(xiàn)算法,旨在找到具有強(qiáng)交互或者共同話題偏好的社群。面向老年人的多源數(shù)據(jù)融合應(yīng)用驗(yàn)證結(jié)合我國人口老齡化的嚴(yán)峻狀況,本文設(shè)計實(shí)現(xiàn)了一個基于多源數(shù)據(jù)融合的社會化用藥提醒應(yīng)用原型系統(tǒng)。該系統(tǒng)借助于多源數(shù)據(jù)可以感知用戶的運(yùn)動和健康狀態(tài),能夠檢測用戶的用藥情況,依據(jù)用戶交互關(guān)系和共同偏好選擇合適的提醒發(fā)起者,實(shí)現(xiàn)自適應(yīng)的用藥提醒。本文從系統(tǒng)架構(gòu)的角度對系統(tǒng)中各個層次的功能需求進(jìn)行闡述,并對原型系統(tǒng)進(jìn)行初步的分析和評估。
[Abstract]:The birth of network technology extends the human interaction extension in the physical space into the virtual information space, overcomes the restriction of space to the human, greatly shortens the time of information transmission and strengthens the interaction between users. With the further development of the perceptual technology and the emergence of the mobile computing terminal, the human activities are in two spaces. Alternately alternately, the interaction between physical space and information space is more frequent, and a large number of digital information is left in the two spaces. The integration of multiple spaces promotes the appearance of Cyber-Physical-Social System (CPSS) in the multisource data space of.CPSS, which has the characteristics of heterogeneity, dynamics, sparsity and high noise, and so on. A number of challenges are presented for data representation, processing and analysis. This paper, taking health data analysis as the application background, studies the extraction of health related semantic information from the perceptual data in the physical space and the online data in the information space. The main research work and creation are as follows: multisource data and the multisource number of its computing models. Space contains a variety of data information. These data are heterogeneous, dynamic, sparse, and high noise. This paper analyzes the characteristics of perceptual data and online data, defines the perceptual data model and the online data model, and realizes the representation and storage of different trait data. In order to realize the mixing of different types of data In this paper, the relationship between different data is abstracted from the ontology representation model and the corresponding calculation model is constructed based on knowledge reasoning. The lightweight perceptual data semantic analysis is possible with the use of a large number of physiological sensing devices, and it is possible to detect and analyze the health status of the users by using the perceptual devices. This paper focuses on the research of the base. First, this paper makes a summary analysis of user behavior recognition from the perspective of perceptual technology and recognition algorithm. This paper focuses on lightweight behavioral analysis methods to achieve long-term monitoring of motion status. This paper starts with sampling frequency, feature selection and algorithm angle. A lightweight hierarchical behavior analysis algorithm is proposed for the characteristics of mobile terminal resource constraints. By reducing the probability of using the sampling frequency and frequency domain data, the balance between the recognition accuracy and the energy consumption is realized. Based on the behavior analysis algorithm, this paper uses the metabolic equivalent analysis method to realize the user's motion state evaluation. The online data health semantic analysis based on word vector is an extension of human physical interaction in the network space, which may imply the user's health information. This paper studies the method of mining user health behavior from a large number of online data, especially text data. The first research on the strategies and parties of online data acquisition is made. A social media data collection platform is constructed to collect data from different social service platforms. Then, the relationship between the online data and the user's health behavior attributes is analyzed from the aspects of interactive features, semantic features and topological features. In this paper, the multisource data fusion problem in CPSS system is studied in this paper. The multisource data fusion method is analyzed from two levels of feature level fusion and decision level fusion. Based on the feature fusion, this paper proposes a community discovery algorithm based on multi source feature, aiming at finding a community with strong interaction or common topic preference. The application verification of multi-source data integration for the elderly combines the grim shape of the aging population in China. In this paper, a social drug reminder application prototype system based on multi source data fusion is designed and implemented. The system can perceive the user's movement and health state with the aid of multi source data, can detect the user's medication situation, and select the appropriate reminder based on the user interaction and common preference, and realize the adaptive drug use. Reminding. From the point of view of system architecture, this paper expounds the functional requirements of all levels in the system, and makes preliminary analysis and evaluation of the prototype system.
【學(xué)位授予單位】：西北工業(yè)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：TP391.1

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