本文關(guān)鍵詞： 語(yǔ)義物聯(lián)網(wǎng) 本體摘要 重要度計(jì)算 RDF語(yǔ)句 鏈接分析　出處：《大連海事大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：針對(duì)物聯(lián)網(wǎng)的內(nèi)在矛盾,將語(yǔ)義協(xié)同過(guò)程引入物聯(lián)網(wǎng),形成新一代網(wǎng)絡(luò),即語(yǔ)義物聯(lián)網(wǎng)。語(yǔ)義協(xié)同過(guò)程是指基于本體進(jìn)行語(yǔ)義標(biāo)注與語(yǔ)義理解,因此,本體在語(yǔ)義物聯(lián)網(wǎng)中起到了核心作用。但是,語(yǔ)義物聯(lián)網(wǎng)本體目前主要存在兩點(diǎn)不足:一是本體數(shù)量過(guò)多、內(nèi)容復(fù)雜,不利于本體工程專家去理解并完成本體重用等相關(guān)工作;二是本體體積過(guò)大,對(duì)于語(yǔ)義物聯(lián)網(wǎng)底層設(shè)備資源能力受限的情況下,能夠提供一個(gè)精簡(jiǎn)且涵蓋了最重要信息的本體是很有必要的。為了解決語(yǔ)義物聯(lián)網(wǎng)本體不利于理解、體積過(guò)大等問(wèn)題,本文提出了一種基于重要度計(jì)算的語(yǔ)義物聯(lián)網(wǎng)本體摘要方法,從而保證語(yǔ)義物聯(lián)網(wǎng)語(yǔ)義協(xié)同過(guò)程的更好實(shí)現(xiàn)。本論文采用結(jié)構(gòu)和語(yǔ)用特征相結(jié)合的方式來(lái)實(shí)現(xiàn)基于重要度計(jì)算的語(yǔ)義物聯(lián)網(wǎng)本體摘要。首先,對(duì)語(yǔ)義物聯(lián)網(wǎng)本體進(jìn)行預(yù)處理,獲取本體中的術(shù)語(yǔ)集、RDF語(yǔ)句集和鏈接類型集,生成初始的RDF語(yǔ)句序列,采用RDF語(yǔ)句作為語(yǔ)義物聯(lián)網(wǎng)本體摘要過(guò)程中的基本語(yǔ)義單元,創(chuàng)建表征本體結(jié)構(gòu)的二分圖模型;接著,在二分圖模型的基礎(chǔ)上,對(duì)RDF語(yǔ)句進(jìn)行基于鏈接分析的結(jié)構(gòu)重要度計(jì)算和基于語(yǔ)用統(tǒng)計(jì)的語(yǔ)用重要度計(jì)算,通過(guò)對(duì)統(tǒng)計(jì)結(jié)果和閾值的比較,進(jìn)行RDF語(yǔ)句綜合重要度計(jì)算,生成按照重要度排序的RDF語(yǔ)句序列,并設(shè)計(jì)了重要度計(jì)算過(guò)程算法;然后,對(duì)按照重要度排序的RDF語(yǔ)句序列進(jìn)行冗余處理,將綜合重要度最高的對(duì)象抽取到摘要結(jié)果集中,按需設(shè)定摘要長(zhǎng)度后,生成摘要后結(jié)果集,并設(shè)計(jì)了摘要生成過(guò)程算法。為了驗(yàn)證上述方法在語(yǔ)義物聯(lián)網(wǎng)中的有效性,本論文最后設(shè)計(jì)并實(shí)現(xiàn)了基于重要度計(jì)算的語(yǔ)義物聯(lián)網(wǎng)本體摘要原型系統(tǒng)。該系統(tǒng)從功能上分為語(yǔ)義物聯(lián)網(wǎng)本體預(yù)處理模塊、語(yǔ)義物聯(lián)網(wǎng)本體重要度計(jì)算模塊及基于重要度的語(yǔ)義物聯(lián)網(wǎng)本體摘要生成模塊,分別實(shí)現(xiàn)了對(duì)語(yǔ)義物聯(lián)網(wǎng)本體的解析、建模,重要度計(jì)算,消除冗余與摘要抽取功能。最終通過(guò)實(shí)驗(yàn)驗(yàn)證了該方法的準(zhǔn)確性、可行性及該原型系統(tǒng)的性能。實(shí)驗(yàn)結(jié)果表明該本體摘要方法可以為用戶提供滿足其偏好的最優(yōu)本體。
[Abstract]:In view of the inherent contradiction of the Internet of things, semantic collaborative process is introduced into the Internet of things to form a new generation of network, namely semantic Internet of things. Semantic collaborative process refers to semantic annotation and semantic understanding based on ontology. Ontology plays a central role in the semantic Internet of things. However, there are two main shortcomings in semantic ontology: first, the number of ontology is too much and the content is complex, which is not conducive to ontology engineering experts to understand and complete ontology reuse and other related work; Secondly, it is necessary to provide a concise ontology that covers the most important information in order to solve the problem that semantic Internet of things is not conducive to understanding, because the ontology is too large, and it is necessary for the semantic Internet of things to provide a concise ontology that covers the most important information under the condition of limited resource capacity of the underlying devices in the semantic Internet of things. In this paper, a semantic Internet of things ontology summary method based on importance calculation is proposed. In order to ensure the better realization of semantic collaborative process of semantic Internet of things. This paper uses the combination of structure and pragmatic features to realize semantic ontology summary based on importance calculation. Firstly, the semantic ontology of Internet of things is preprocessed. The RDF statement set and link type set are obtained, and the initial sequence of RDF statements is generated. The RDF statement is used as the basic semantic unit in the process of semantic ontology summary, and the bipartite graph model is created to represent the ontology structure. On the basis of bipartite graph model, we calculate the structural importance of RDF sentences based on link analysis and pragmatic statistics based on pragmatic statistics. By comparing the statistical results and threshold values, we calculate the comprehensive importance degree of RDF sentences. The sequence of RDF statements sorted according to the importance degree is generated, and the algorithm for calculating the importance degree is designed. Then, the sequence of RDF statements sorted according to the importance degree is processed by redundancy, and the objects with the highest synthetic importance are extracted into the summary result set. After the length of the summary is set according to the need, the result set is generated, and the algorithm of the process is designed. In order to verify the effectiveness of the above method in the semantic Internet of things, In the end of this thesis, the prototype system of semantic ontology abstracting based on importance computing is designed and implemented, which is divided into semantic ontology preprocessing module. The semantic Internet of things ontology importance calculation module and the semantic Internet of things ontology summary generation module based on the importance of the semantic Internet of things ontology analysis, modeling, importance calculation, respectively, Finally, the accuracy and feasibility of the method and the performance of the prototype system are verified by experiments. The experimental results show that the proposed method can provide users with the best ontology to satisfy their preferences.
【學(xué)位授予單位】：大連海事大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.1;TP391.44;TN929.5

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