本文選題：Folksonomy + 關系頻次��； 參考：《東北師范大學》2017年碩士論文

【摘要】：自2004年被托馬斯·范德·沃爾(Thomas Vander Wal)首次提出“Folksonomy”這一概念以來,Folksonomy知識組織模式被各種類型的資源網(wǎng)站用以組織架構(gòu)網(wǎng)站資源。Folksonomy知識組織模式區(qū)別于其他傳統(tǒng)知識組織體系,它是在現(xiàn)代開放語義網(wǎng)絡環(huán)境下由用戶個體自由參與標注,而并非由領域權威制定規(guī)則,因此表現(xiàn)出混沌離散的外在表象。也正是因為這一原因,在學術界也掀起了Folksonomy知識組織模式的研究熱潮。目前的研究工作中,采用網(wǎng)絡思維構(gòu)建標簽知識網(wǎng)絡進行Folksonomy知識組織模式相關研究的方法已經(jīng)被學術界接受并認可。由于Folksonomy知識組織模式采用社會化標注形式,因此相關的研究工作往往需要面臨海量數(shù)據(jù)的處理。當面對巨量數(shù)據(jù)的分析研究時,在獲得大數(shù)據(jù)思維帶來的優(yōu)勢時,不得不同時考慮大數(shù)據(jù)所面臨的“低價值”問題。畢竟開放的網(wǎng)絡環(huán)境加上自由的社會化標注,使得Folksonomy知識組織模式中的社會化標簽中充斥著大量的模糊的、歧義的、甚至錯誤的信息。一些相關的研究工作中往往由研究者自行設定閾值對數(shù)據(jù)進行篩選。盡管這種處理方式在一定程度上保障了數(shù)據(jù)的顯著性和有效性,但同時也面臨著其他問題。首先,閾值的設定缺少必要的理論保障。其次,根據(jù)閾值提取的數(shù)據(jù)與原始數(shù)據(jù)是否具有等效性。再次,當面臨多個時段或多個類型問題的研究時是否具有可比性。因此,探索一種保障數(shù)據(jù)顯著性的同時具有堅實的理論支撐,能夠保障所提取的層次知識網(wǎng)絡與原始知識網(wǎng)絡等效,且具有一定可比性的層次知識網(wǎng)絡提取方法成為學術界亟待解決的問題。本文采用德國Kassel大學的知識與數(shù)據(jù)工程小組架設與維護的系統(tǒng)BibSonomy為數(shù)據(jù)源,從中采集5組領域知識數(shù)據(jù)集�；跇撕灥耐F(xiàn)關系,構(gòu)建領域知識網(wǎng)絡。對知識網(wǎng)絡中關聯(lián)關系的頻度分布進行統(tǒng)計分析。在此基礎上根據(jù)冪律分布與分形理論,基于知識關聯(lián)頻度設定閾值,提取知識層次網(wǎng)絡�？紤]到學術界的前期研究已經(jīng)證實基于標簽同現(xiàn)構(gòu)建的領域知識網(wǎng)絡的度分布具有冪律分布特征,而且網(wǎng)絡具有小世界效應,因此研究中對所提取的層次知識網(wǎng)絡主要從度值的冪律分布和網(wǎng)絡小世界效應兩個方面進行測試。研究結(jié)果表明,以知識關聯(lián)頻度為閾值提取的層次知識網(wǎng)絡具有良好的冪律分布特征(無標度網(wǎng)絡)和小世界效應,驗證了層次知識網(wǎng)絡與原始知識網(wǎng)絡的等效性。因此,Folksonomy知識組織模式中,以知識關聯(lián)頻度為閾值提取的層次知識網(wǎng)絡具有原始網(wǎng)絡的整體性征。
[Abstract]:Since the concept of Folksonomy was first introduced by Thomas van der Walder Thomas Vander Walder in 2004, the knowledge organization model of Folksonomy has been used by various types of resource sites to organize the web site resources. The knowledge organization pattern of folksonomy is different from other traditional knowledge organization systems. In the modern open semantic network environment, the user is free to participate in tagging, not by the authority of the domain to make rules, so it shows the appearance of chaos discretization. It is for this reason that the research of knowledge organization mode of Folksonomy has been launched in academic circles. In the current research work, the method of using network thinking to construct tag knowledge network for Folksonomy knowledge organization pattern has been accepted and recognized by academic circles. Because Folksonomy knowledge organization pattern adopts the form of social tagging, the related research work often faces the processing of massive data. In the face of the analysis of huge amount of data, we have to consider the "low value" problem faced by big data when we get the advantage of big data thinking. After all, the open network environment and free social tagging make the social tags in the Folksonomy knowledge organization model full of vague, ambiguous, and even wrong information. In some related research work, researchers often set their own threshold to filter the data. Although this method ensures the significance and validity of the data to some extent, it also faces other problems. First of all, the threshold setting lacks the necessary theoretical guarantee. Secondly, whether the data extracted according to the threshold is equivalent to the original data. Third, whether there is comparability when facing multiple time periods or multiple types of problems. Therefore, to explore a method to ensure the salience of the data has solid theoretical support, which can guarantee the equivalence of the extracted hierarchical knowledge network with the original knowledge network. And a certain comparable hierarchical knowledge network extraction method has become an urgent problem in academia. BibSonomy, a knowledge and data engineering system set up and maintained by Kassel University in Germany, is used as a data source to collect five sets of domain knowledge data sets. Based on the cooccurrence relation of label, the domain knowledge network is constructed. The frequency distribution of association relation in knowledge network is analyzed statistically. Based on the power law distribution and fractal theory, the threshold is set based on the frequency of knowledge association, and the knowledge hierarchy network is extracted. Considering that previous studies in academia have proved that the degree distribution of domain knowledge networks based on label cooccurrence is characterized by power-law distribution and that networks have small-world effects, Therefore, the extracted hierarchical knowledge networks are mainly tested from the power law distribution of degree values and the network small world effect. The results show that the hierarchical knowledge network with knowledge association frequency as the threshold has good power law distribution (scale-free network) and small world effect, which verifies the equivalence between hierarchical knowledge network and original knowledge network. Therefore, in the knowledge organization pattern of Folksonomy, the hierarchical knowledge network, which is extracted from the frequency of knowledge association as the threshold, has the integrity of the original network.
【學位授予單位】：東北師范大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：O157.5

【參考文獻】

相關期刊論文 前10條

1 李金海;何有世;馬云蕾;;基于領域本體的在線評論信息層次化挖掘[J];系統(tǒng)工程;2016年10期

2 滕廣青;常志遠;劉雅姝;趙汝南;張利彪;;Folksonomy知識組織模式中領域知識動態(tài)演化規(guī)律研究[J];圖書與情報;2016年04期

3 滕廣青;楊明秋;田依林;黃微;;Folksonomy模式中的知識群落及其核心知識分析[J];圖書情報工作;2015年22期

4 羅琳;梁桂生;蔡軍;;基于分眾分類法的圖書館書目推薦系統(tǒng)[J];現(xiàn)代圖書情報技術;2014年04期

5 劉向;馬費成;王曉光;;知識網(wǎng)絡的結(jié)構(gòu)及過程模型[J];系統(tǒng)工程理論與實踐;2013年07期

6 劉海旭;鄭巖;;基于語義的標簽關聯(lián)算法[J];軟件;2012年12期

7 賈君枝;張寧;;社會標簽的應用功能分析[J];情報理論與實踐;2012年11期

8 蘇曉萍;樓俊鋼;;結(jié)合超圖投影和隨機游走的個性化推薦方法[J];情報學報;2012年08期

9 吳江;;自由分類標簽類聚成網(wǎng)狀分類結(jié)構(gòu)研究與實現(xiàn)[J];圖書情報知識;2011年01期

10 李超;;一種基于主題和分眾分類的信息檢索優(yōu)化方法[J];情報理論與實踐;2009年10期

，

本文編號：2026162