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研究生:曾俊維
研究生(外文):TSENG, CHUN-WEI
論文名稱:運用圖形資料庫進行地理資訊系統之建置—以東京地鐵為例
論文名稱(外文):A Construction of Geographic Information System by Graph Database─Using Tokyo Metro System as an Example
指導教授:曾守正曾守正引用關係周韻寰周韻寰引用關係
指導教授(外文):TSENG, SHOU-CHENGCHOU, YUN-HUAN
口試委員:曾守正周韻寰黃文楨吳大鈞
口試委員(外文):TSENG, SHOU-CHENGCHOU, YUN-HUANHUANG, WEN-CHENWu, DA-CHUN
口試日期:2017-06-16
學位類別:碩士
校院名稱:國立高雄第一科技大學
系所名稱:資訊管理系碩士班
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:中文
論文頁數:71
中文關鍵詞:NoSQL圖形資料庫Neo4j東京地下鐵路社群網路
外文關鍵詞:NoSQLGraph DatabaseNeo4jTokyo Metro SystemSocial Analysis
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隨著資訊科技日益進步,每天產出的資訊量不斷擴大,為因應日漸龐大的資訊量與多元的資料型態,資料庫相關技術也不斷革新,衍生出NoSQL跳脫傳統的綱要 (Schema) 框架限制、被賦予更高的彈性。例如,圖形資料庫可以使用節點與節點之間的關係建立資料之間的圖形結構,並提供查詢節點之間的親疏關係以及鄰近節點,或是節點之間最短距離等的相關語法。本研究即是使用圖形資料庫來建置地理資訊系統,將繁複的東京地鐵路線以目前最受歡迎的圖形資料庫軟體Neo4j來處理,並將地鐵路線各車站定點標示於地圖相對位置,以利查詢應用及社群分析應用,降低搭乘東京地鐵的困難,解決乘客在東京地鐵各站轉乘的煩惱。整個研究的目標是:希望藉由東京地鐵地理資訊系統的建置經驗,了解在建置串連台灣鐵路、捷運,甚至公共汽車、藍色公路的交通資訊系統時可能遭遇的問題,進而找到解決的方法,改善台灣整體的交通環境,讓台灣成為智慧城市,提振台灣的整體經濟效益。
關鍵詞:NoSQL、圖形資料庫、Neo4j、東京地下鐵路、社群網路。
With the escalating progress of information and communication technology, the daily output of information is expanding, in response to the ever-increasing amount of information and diverse data types, the database technology is also innovative, e.g., the NoSQL technology alleviates traditional approach by a schema-less framework, which gains the merit of higher flexibility, such that the graph databases offer users to create nodes, together with their connected relationships. Besides, users can issue intuitive and versatile query statements to retrieve the relationships between nodes, or the shortest path between nodes. This study will employ the most popular graph database, Neo4j, to build a geographic information system of Tokyo Metro network. We intend to mark the station information on the map to show their relative positions, to facilitate the application of community analysis and reduce the passengers’ obsession. The aim of this study is to learn how the follow-up can be applied to the railways and MRTs of Taiwan as a whole. For future integration, we intend to take the bus and even blue ocean pathways into account in the future. This testbed plays hopefully an important base for the future development of the smart city or the overall tourism environment in Taiwan to boost overall gross national profit and efficiency.
Keywords: NoSQL, Graph Database, Neo4j, Tokyo Metro System, Social Analysis.
目 錄
中文摘要 i
ABSTRACT ii
誌 謝 iii
目 錄 iv
圖目錄 vi
表目錄 vii
一、 緒 論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 論文架構 2
二、 文獻探討 3
2.1 NoSQL 3
2.1.1 NoSQL的基礎理論 3
2.1.2 NoSQL的特徵 4
2.1.3 NoSQL的類型 5
2.2 Neo4j 6
2.3 適地性服務Location Based Services (LBS) 10
三、 研究方法 11
3.1 系統流程與架構 11
3.2 東京地下鐵路 11
3.2.1 東京地下鐵 (Tokyo Metro / 東京メトロ) 12
3.2.2 都營地下鐵 (都営地下鉄) 14
3.2.3 東京地區其他重要路線 15
3.2.4 東京地鐵複雜站點解析 16
四、 實驗建置與結果分析 18
4.1 系統環境與建置 18
4.2 資料庫建置與Cypher查詢測試 19
4.3 系統實作 29
4.3.1 連接後端伺服器與Neo4j 29
4.3.2 資料與地圖結合應用 31
五、 結論與未來研究 34
5.1 結論 34
5.2 未來研究 34
參考文獻 35
附錄一:東京地鐵系統全圖 37
附錄二:東京地下鐵路系統車站資訊 38
附錄三:東京地下鐵路系統車站間關係資訊 52
附錄四:東京地下鐵路系統車站間連線資訊 60
附錄五:東京地鐵指令查詢處理程式碼 68
附錄六:地鐵站點地圖標記前端資料處理 69


參考文獻
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[3]Caldarola, E.G., Picariello, A., and Rinaldi, A.M. “Big Graph-Based Data Visualization Experiences: The WordNet Case Study. In Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K),” Proceedings of the 2015 IEEE International on 7th Joint Conference, Vol. 1, November 2015, pp. 104-115.
[4]Chen, P. P. S. “The Entity-Relationship Model—Toward a Unified View of Data,” ACM Transactions on Database Systems (TODS), Vol. 1, Issue 1, March 1976, pp. 9-36.
[5]Fox, A., Gribble, S. D., Chawathe, Y., Brewer, E. A., and Gauthier, P. “Cluster-Based Scalable Network Services,” ACM SIGOPS Operating Systems Review, Vol. 31, No. 5, October 1997, pp. 78-91.
[6]Gilbert, S., and Lynch, N. “Brewer's Conjecture and the Feasibility of Consistent, Available, Partition-Tolerant Web Services,” ACM SIGACT News, Vol. 33, Issue 2, June 2002, pp. 51-59.
[7]Gilbert, S., and Lynch, N. “Perspectives on the CAP Theorem,” IEEE Computer, Vol. 45, No. 2, Jan. 2012, pp. 30-36.
[8]Google's BigTable, Last access: 2017-3-31. (Available online at http://andrewhitchcock.org/?post=214)
[9]Gray, J. “The Transaction Concept: Virtues and Limitations,” Proceedings of the International Conference on Very Large Data Bases, Vol. 7, September 1981, pp. 144-154.
[10]Jiang, L., Yue, P., and Guo, X. “Semantic Location-Based Services,” Proceedings of the 2016 IEEE International on Geoscience and Remote Sensing Symposium (IGARSS), July 2016, pp. 3606-3609.
[11]Joshi, H., and Bamnote, G. R. “Distributed Database: A Survey,” the International Journal of Computer Science and Applications, Vol. 6, No. 2, Apr. 2013, pp. 289-292.
[12]Jouili, S., and Vansteenberghe, V. “An Empirical Comparison of Graph Databases,” Proceedings of the 2013 IEEE International Conference on Social Computing (SocialCom), September 2013, pp. 708-715.
[13]Tokyo Metro, Last access: 2017-3-31. (Available online at http://www.tokyometro.jp/tcn/)
[14]Vicknair, C., Macias, M., Zhao, Z., Nan, X., Chen, Y., and Wilkins, D. “A Comparison of a Graph Database and a Relational Database: A Data Provenance Perspective,” Proceedings of the 48th ACM Annual Southeast Regional Conference, April 2010, pp. 42.
[15]Webber, J. “A Programmatic Introduction to Neo4j,” Proceedings of the 3rd ACM Annual Conference on Systems, Programming, and Applications: Software for Humanity, October 2012, pp. 217-218.
[16]東京都交通局,Last access: 2017-3-31. (available online at https://www.kotsu.metro.tokyo.jp/)
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