本文選題：地理信息系統(tǒng) + 地理信息鏈接��； 參考：《華北電力大學(xué)(北京)》2017年碩士論文

【摘要】：GIS是最近二十多年來新興的一門集地理信息科學(xué)、計(jì)算機(jī)科學(xué)、測(cè)繪科學(xué)和統(tǒng)計(jì)科學(xué)等于一體的一門綜合性學(xué)科,是用于輸入、存儲(chǔ)、查詢、分析和展示地理數(shù)據(jù)的信息系統(tǒng),以便及時(shí)解決地理信息處理中復(fù)雜的規(guī)劃和管理問題。目前,GIS技術(shù)已經(jīng)廣泛的應(yīng)用在各種的領(lǐng)域當(dāng)中,GIS和應(yīng)用模型的集成以及GIS智能化是拓寬GIS應(yīng)用領(lǐng)域的關(guān)鍵。在地理信息系統(tǒng)中,不同地理信息源的內(nèi)容之間的多樣性、異構(gòu)性等對(duì)地理信息實(shí)體描述的準(zhǔn)確性、完整性等有很大的差異,這對(duì)實(shí)現(xiàn)地理信息共享以及促進(jìn)地理信息技術(shù)的發(fā)展都產(chǎn)生了阻礙。不同地理信息源的地理信息實(shí)體之間鏈接的精確性對(duì)解決地理信息異構(gòu)性,促進(jìn)地理信息檢索服務(wù)的準(zhǔn)確性和地理信息集成等問題具有十分重要的意義。目前,大多數(shù)的研究工作基于語義關(guān)系、信息內(nèi)容、上下文信息等來計(jì)算地理信息實(shí)體的相似性,忽略了地理空間關(guān)系和空間拓?fù)浣Y(jié)構(gòu)的作用。本文提出了一種基于空間關(guān)系、實(shí)體名稱和實(shí)體類別等多特征的方式,同時(shí)結(jié)合語義和機(jī)器學(xué)習(xí)的方法實(shí)現(xiàn)的地理信息鏈接的半自動(dòng)化方式。首先,分別從三個(gè)地理信息源:OpenStreetMap、Wikimapia、Google places抽取地理信息,抽取的地理信息主要針對(duì)美國(guó)洛杉磯和英國(guó)倫敦兩個(gè)地區(qū)的城區(qū)建筑。其次,分析抽取地理信息數(shù)據(jù)的特點(diǎn)構(gòu)建地理信息本體,通過地理信息源數(shù)據(jù)與地理信息本體映射,實(shí)現(xiàn)地理數(shù)據(jù)的一體化。最后,分別討論融合分類算法支持向量機(jī)、K近鄰方法的鏈接方法,同時(shí)與Samal等人提出的鏈接方法進(jìn)行對(duì)比,多角度綜合驗(yàn)證本文提出方法的準(zhǔn)確性,為地理信息集成奠定了良好的基礎(chǔ)。
[Abstract]:GIs is an integrated subject that integrates geographic information science, computer science, mapping science and statistical science. It is an information system for input, storage, query, analysis and display of geographic data. In order to solve the complex planning and management problems in geographic information processing in time. At present, GIS technology has been widely used in various fields of GIS and application model integration and GIS intelligence is the key to broaden the application of GIS. In GIS, the diversity and heterogeneity of the contents of different geographic information sources have great differences in the accuracy and completeness of the description of geographic information entities. This hinders the realization of geographic information sharing and the development of geographic information technology. The accuracy of the links between geographic information entities from different geographic information sources is of great significance in solving the problems of geographic information heterogeneity, promoting the accuracy of geographic information retrieval services and geographic information integration. At present, most of the research work based on semantic relations, information content, context information to calculate the similarity of geographic information entities, ignoring the role of geospatial relationships and spatial topology. In this paper, a semi-automatic method of geographic information link based on spatial relationship, entity name and entity category is proposed, which combines semantic and machine learning methods. First of all, three geographic information sources: OpenStreetMap WikimapiaGoogle places are extracted, which are mainly aimed at the urban buildings in Los Angeles and London. Secondly, the characteristics of extracting geographic information data are analyzed to construct geographical information ontology, and the integration of geographical data is realized by mapping geographical information source data with geographic information ontology. Finally, the link method of the fusion classification algorithm support vector machine / K-nearest neighbor method is discussed, and compared with the link method proposed by Samal et al., the accuracy of the proposed method is verified by multi-angle synthesis. It lays a good foundation for geographic information integration.
【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：P208;TP181

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本文編號(hào)：2096194