旅游文本地名熱度及其共現(xiàn)關(guān)系計(jì)算方法
發(fā)布時(shí)間：2018-11-07 06:42
【摘要】：旅游地空間結(jié)構(gòu)研究是旅游地理學(xué)中重要的研究內(nèi)容。隨著信息化、網(wǎng)絡(luò)化的發(fā)展,旅游地的發(fā)展不再是局限于較為封閉的環(huán)境,對于旅游地空間結(jié)構(gòu)的研究也不能只局限于官方數(shù)據(jù)和區(qū)位因素分析�！氨姲蹦Ｊ降恼Q生使得網(wǎng)絡(luò)上可以利用的旅游地?cái)?shù)據(jù)日益豐富,包括微博、簽到、照片、興趣點(diǎn)等帶有位置的服務(wù)豐富了越來越多研究者的研究工作。本文的基礎(chǔ)數(shù)據(jù)是眾包旅游文本,以期構(gòu)建一套完整的思路和方法,能夠充分深入的挖掘蘊(yùn)含在旅游文本集合中的旅游地空間結(jié)構(gòu)信息。本文以九寨溝為實(shí)例利用提出的思路和方法及封裝好的應(yīng)用工具,完成了從數(shù)據(jù)準(zhǔn)備、流程設(shè)計(jì)到分類分析的一套完整過程,其結(jié)果證明了方法的可行性及價(jià)值。本文提出的主要研究思路和方法介紹如下。在計(jì)算方法上,針對眾包旅游文本中蘊(yùn)含著大量有待挖掘的旅游者時(shí)空行為信息的問題,在研究組前期工作的基礎(chǔ)上,創(chuàng)新的提出基于文本集合的地名權(quán)重分配、地名詞頻與共現(xiàn)矩陣相結(jié)合的計(jì)算方法,加入社會及城市網(wǎng)絡(luò)分析等方法,能夠深入挖掘眾包旅游文本中的地名信息。在思路上,為系統(tǒng)研究旅游地空間結(jié)構(gòu)信息,創(chuàng)新的提出利用旅游文本完成旅游地內(nèi)部聯(lián)系及其與外部聯(lián)系模式的研究。獲取的旅游地地名間的共現(xiàn)關(guān)系以共現(xiàn)矩陣和三元組共同存儲的方式,便于依據(jù)不同的研究需求,提取多研究視角下的共現(xiàn)關(guān)系子集。結(jié)果分析實(shí)現(xiàn)了統(tǒng)計(jì)圖、表和地圖可視化的結(jié)合,并不斷嘗試進(jìn)行科學(xué)的表現(xiàn)方式,盡量使數(shù)據(jù)和信息成為有效的知識,發(fā)揮旅游文本研究的最大價(jià)值。以九寨溝為例做實(shí)證研究,實(shí)現(xiàn)了九寨溝旅游地?zé)岫鹊孛詣犹崛?旅游地?zé)岫鹊孛g、特定景觀間的共現(xiàn)關(guān)系的量化和可視化。其中九寨溝與外部聯(lián)系模式研究,實(shí)現(xiàn)了九寨溝與省內(nèi)、省外熱度城市名、省內(nèi)旅游地名之間三類共現(xiàn)關(guān)系的可視化。研究得出結(jié)論:熱度地名及其共現(xiàn)關(guān)系能夠清晰表現(xiàn)文本作者群體對九寨溝旅游地內(nèi)部景觀和外部空間關(guān)系的認(rèn)知結(jié)構(gòu)。例如,九寨溝旅游地與北京、上海、成都等省內(nèi)外客源地旅游城市的聯(lián)系強(qiáng)度;九寨溝與松潘、茂縣、汶川等支撐服務(wù)城市的聯(lián)系,以及和黃龍、都江堰、峨眉山等同省旅游地的聯(lián)系特征等。九寨溝內(nèi)部聯(lián)系模式研究,實(shí)現(xiàn)了各景區(qū)、各類景觀的整體及分層分析。研究得出結(jié)論:(1)景觀的網(wǎng)絡(luò)連接度和景觀的關(guān)注等級呈現(xiàn)出三種模式,但總體呈一定的正相關(guān)關(guān)系。(2)九寨溝旅游地內(nèi)部分區(qū)、分類、集聚存在明顯特征。三大景區(qū)之間存在著差異;景觀類型的發(fā)展存在差異;空間具有核心引導(dǎo)與集聚現(xiàn)象,具體表現(xiàn)為三大核心、兩大集聚景群。研究結(jié)果表明:(1)該方法能夠適應(yīng)旅游地理和相關(guān)學(xué)科對旅游文本內(nèi)容挖掘的研究需求;(2)挖掘結(jié)果對特定群體的旅游空間感知特征與結(jié)構(gòu)有顯著的表征意義。
[Abstract]:The study of tourism spatial structure is an important research content in tourism geography. With the development of information technology and network, the development of tourist destination is no longer confined to a relatively closed environment, nor can the study of spatial structure of tourist destination be confined to official data and analysis of location factors. With the emergence of crowdsourcing model, more and more research work has been done by more and more researchers, such as Weibo, check-in, photos, interest points and other services with location. The basic data of this paper is crowdsourcing tourism text, in order to build a complete set of ideas and methods, can fully mining the tourism text contained in the set of tourism spatial structure information. This paper takes Jiuzhaigou as an example to complete a complete process from data preparation, process design to classification analysis by using the ideas and methods proposed and the encapsulated application tools. The results prove the feasibility and value of the method. The main research ideas and methods proposed in this paper are as follows. In terms of calculation methods, aiming at the problem that there are a lot of spatio-temporal behavior information of tourists to be excavated in the text of crowdsourcing tourism, on the basis of the previous work of the study group, the paper proposes the distribution of geographical names weight based on text set. The method of calculating the frequency of place names and the co-occurrence matrix, and adding the methods of social and urban network analysis, can deeply excavate the toponymic information in the text of crowdsourcing tourism. In order to systematically study the spatial structure information of tourist destination, the paper proposes to use tourism text to complete the research of the internal connection and the external contact mode of tourism destination. The co-occurrence relation among tourist destination place names is stored in the form of co-occurrence matrix and triple, which is convenient to extract the subset of co-occurrence relation from multiple perspectives according to different research requirements. Results the analysis realized the combination of statistical chart, table and map visualization, and tried to make the data and information become the effective knowledge as far as possible, and give play to the greatest value of the tourism text research. Taking Jiuzhaigou as an example, the paper realizes the automatic extraction of the heat degree place names, the quantification and visualization of the co-occurrence relationship between the heat degree place names and the specific landscape in Jiuzhaigou. The research of Jiuzhaigou and external connection model realizes the visualization of three kinds of co-occurrence relations between Jiuzhaigou and the province, the city name of heat degree outside the province, and the tourist place name in the province. The conclusion of the study is that the relationship between heat place names and their co-occurrence can clearly express the cognitive structure of the text author group on the relationship between the internal landscape and the external space of Jiuzhaigou tourist destination. For example, Jiuzhaigou tourist destination and Beijing, Shanghai, Chengdu and other tourist cities within and outside the source of tourism intensity; Jiuzhaigou and Songpan, Maoxian, Wenchuan and other supporting service cities, as well as Huanglong, Dujiangyan, Emei mountain equivalent of tourism links and so on. Jiuzhaigou internal contact model research, achieve all scenic spots, all kinds of landscape overall and hierarchical analysis. The conclusions are as follows: (1) the degree of network connectivity and the attention level of landscape show three patterns, but there is a positive correlation in the whole. (2) there are obvious characteristics in the interior of Jiuzhaigou tourist destination. There are differences among the three scenic spots; there are differences in the development of landscape types; the space has the phenomenon of core guidance and agglomeration. The results show that: (1) the method can meet the research needs of tourism text content mining in tourism geography and related disciplines; (2) the results of mining have significant representation significance to the characteristics and structure of tourism spatial perception of a specific group.
【學(xué)位授予單位】：河北師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F592.7;P281
[Abstract]:The study of tourism spatial structure is an important research content in tourism geography. With the development of information technology and network, the development of tourist destination is no longer confined to a relatively closed environment, nor can the study of spatial structure of tourist destination be confined to official data and analysis of location factors. With the emergence of crowdsourcing model, more and more research work has been done by more and more researchers, such as Weibo, check-in, photos, interest points and other services with location. The basic data of this paper is crowdsourcing tourism text, in order to build a complete set of ideas and methods, can fully mining the tourism text contained in the set of tourism spatial structure information. This paper takes Jiuzhaigou as an example to complete a complete process from data preparation, process design to classification analysis by using the ideas and methods proposed and the encapsulated application tools. The results prove the feasibility and value of the method. The main research ideas and methods proposed in this paper are as follows. In terms of calculation methods, aiming at the problem that there are a lot of spatio-temporal behavior information of tourists to be excavated in the text of crowdsourcing tourism, on the basis of the previous work of the study group, the paper proposes the distribution of geographical names weight based on text set. The method of calculating the frequency of place names and the co-occurrence matrix, and adding the methods of social and urban network analysis, can deeply excavate the toponymic information in the text of crowdsourcing tourism. In order to systematically study the spatial structure information of tourist destination, the paper proposes to use tourism text to complete the research of the internal connection and the external contact mode of tourism destination. The co-occurrence relation among tourist destination place names is stored in the form of co-occurrence matrix and triple, which is convenient to extract the subset of co-occurrence relation from multiple perspectives according to different research requirements. Results the analysis realized the combination of statistical chart, table and map visualization, and tried to make the data and information become the effective knowledge as far as possible, and give play to the greatest value of the tourism text research. Taking Jiuzhaigou as an example, the paper realizes the automatic extraction of the heat degree place names, the quantification and visualization of the co-occurrence relationship between the heat degree place names and the specific landscape in Jiuzhaigou. The research of Jiuzhaigou and external connection model realizes the visualization of three kinds of co-occurrence relations between Jiuzhaigou and the province, the city name of heat degree outside the province, and the tourist place name in the province. The conclusion of the study is that the relationship between heat place names and their co-occurrence can clearly express the cognitive structure of the text author group on the relationship between the internal landscape and the external space of Jiuzhaigou tourist destination. For example, Jiuzhaigou tourist destination and Beijing, Shanghai, Chengdu and other tourist cities within and outside the source of tourism intensity; Jiuzhaigou and Songpan, Maoxian, Wenchuan and other supporting service cities, as well as Huanglong, Dujiangyan, Emei mountain equivalent of tourism links and so on. Jiuzhaigou internal contact model research, achieve all scenic spots, all kinds of landscape overall and hierarchical analysis. The conclusions are as follows: (1) the degree of network connectivity and the attention level of landscape show three patterns, but there is a positive correlation in the whole. (2) there are obvious characteristics in the interior of Jiuzhaigou tourist destination. There are differences among the three scenic spots; there are differences in the development of landscape types; the space has the phenomenon of core guidance and agglomeration. The results show that: (1) the method can meet the research needs of tourism text content mining in tourism geography and related disciplines; (2) the results of mining have significant representation significance to the characteristics and structure of tourism spatial perception of a specific group.
【學(xué)位授予單位】：河北師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F592.7;P281
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2 徐丹;;旅游文本英譯技巧研究[J];科技信息;2009年36期
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