博碩士論文 107022605 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:8 、訪客IP:44.220.44.148
姓名 卡雅妮(REGITA PRAMESTI NUR CAHYANI)  查詢紙本館藏   畢業系所 遙測科技碩士學位學程
論文名稱 基於本體論與使用者興趣之個人化地理網路搜尋引擎
(GeoWeb Search Engine Personalization based on Ontology and User Interest)
相關論文
★ 物聯網制動功能之互操作性解決方案★ 地理網路爬蟲:具擴充及擴展性之地理網路資源爬行架構
★ TDR監測資訊平台之改善與 感測器觀測服務之建立★ 利用高解析衛星立體像對產製近岸水底地形
★ 整合oneM2M 及OGC SensorThings API 標準建立開放式物聯網架構★ 巨量物聯網資料之多重屬性索引架構
★ 高效率異質性時序資料表示法辨別系統★ A TOA-reflectance-based Spatial-temporal Image Fusion Method for Aerosol Optical Depth Retrieval
★ An Automatic Embedded Device Registration Procedure for the OGC SensorThings API★ 利用本體論整合城市模型及物聯網開放式標準探討智慧城市之應用
★ 運用無人機及影像套合法進行混凝土橋梁裂縫檢測★ GeoRank: A Geospatial Web Ranking Algorithm for a GeoWeb Search Engine
★ 應用高時空解析度遙測影像融合於海水覆蓋率之監測★ LoRaWAN Positioning based on Time Difference of Arrival and Differential Correction
★ 類神經網路逆向工程理解遙測資訊:以Landsat 8植被分類為例★ 基於語意網技術與WordNet促進地理網路資源之探索
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 摘 要
地理網路(geospatial Web, GeoWeb)表示包含地理空間要素的網路資源,如地圖、地理編碼照片、供應地理資料的網路服務等。如同一般網路資源,地理網路資源散布整個網際網路,使得辨識及整合地理網路資源成為一個艱巨挑戰的任務。為了促進地理資源的發現及重複利用,我們需要地理網路爬蟲主動探索資源並建立一個地理網路搜尋引擎以供查詢及排序結果。然而,為了進一步增進資源的搜尋效能,我們認為理解地理網路資源的語意和網路使用者興趣以提供個人化的搜尋結果極其重要。因此,本研究首先設計地理網路資源的本體論(Ontology),結合多個領域本體的概念來表示地理網路資源。本體論有助於對應與探索概念間的語意關係。地理網路資源本體論亦可幫助語意化(Semanticization)使用者搜尋歷史以建立使用者模型以代表使用者的偏好。最後,當搜尋引擎接收到使用者的查詢,該查詢則基於地理網路本體論和使用者模型進行個人化擴充,進而找到語意相似且符合使用者偏好的搜索結果。再透過比對地理網路資源之語意設計適當的排序機制,幫助使用者有效地找到所欲搜尋的和相關的地理網路資源。實驗分為三組使用者,第一組為五位訓練查詢數量不同的模擬使用者、第二組為五位訓練查詢數量相同的模擬使用者、第三組為十位不受限制的真實使用者,其正規化衡量搜尋引擎質量指標(Normalized Discounted Cumulative Gain, NDCG)值分別為0.97、0.97、及0.85。整體而言,實驗結果顯示所提出的地理網路個人化搜尋方法能夠有效地根據使用者偏好找尋並排序相關的地理網路資源。
摘要(英) ABSTRACT
Geospatial Web (GeoWeb) represents the collection of Web resources that contain geospatial components, such as maps, geocoded images, Web services hosting geospatial data, etc. Similar to general Web resources, GeoWeb resources are scattered on Internet, where the identification and integration of GeoWeb resources become a challenging task. To facilitate geospatial resource discovery, we need GeoWeb Crawlers to proactively discover GeoWeb resources, and establish a GeoWeb search engine to provide querying and ranking mechanisms. However, to further improve resource discovery efficiency, we believe that understanding semantic meanings of GeoWeb resources as well as user interest is important to provide personalized search results. Therefore, in this study, we first design a GeoWeb resource ontology, which contains necessary concepts from many domain ontologies to represent a GeoWeb resource. This ontology helps map and discover semantic relationships between concepts. The GeoWeb resource ontology also helps semanticize a user’s search history to construct a user model representing important concepts to the user. Finally, when receiving a user query, the query is extended based on the GeoWeb ontology and the user model. In this case, semantic-similar and personalized search results can be found. By comparing with the semantic of GeoWeb resources, a proper ranking algorithm is designed to help users find targeted and related GeoWeb resources efficiently. In the result, two experiments of artificial users and one experiment of real users show that the proposed solution achieves 0.97, 0.97, and 0.85 Normalized Discounted Cumulative Gain (NDCG) values. Overall, the experimental result shows that the proposed solution is able to discover and rank relevant resources according to users’ interest.
關鍵字(中) ★ 地理網路搜尋引擎
★ 個人化
★ 語意
★ 本體論
★ 排序
關鍵字(英) ★ GeoWeb search engine
★ personalization
★ semantics
★ ontology
★ ranking
論文目次 Table of Contents
摘 要 ii
ABSTRACT iii
Acknowledgements iv
Table of Contents v
List of Figures and Illustration vii
List of Tables viii
1. Introduction 1
2. Related Work 5
2.1 GeoWeb Crawler and GeoWeb Search Engine 5
2.2 GeoWeb Search Engine Semanticization 5
2.3 GeoWeb Personalization 6
3. Methodology 7
3.1 Personalized GeoWeb Search Engine System Overview 7
3.2 GeoWeb Resource Ontology and GeoWeb Linked-Data 9
3.3 Pre-processing 11
3.3.1 Stopping Word Removal 11
3.3.2 Tokenization 12
3.4 Semanticization 12
3.5 User Model and Resource Model 13
3.5.1 User Model 13
3.5.2 Resource Model 16
3.6 Personalized Query 17
3.7 Weight Determination and Personalized Ranking 19
3.7.1 Weight Determination 19
3.7.2 Personalized Ranking 23
4. Results and Discussion 25
4.1 System evaluation 25
4.1.1 Evaluation scenario 25
4.1.2 Evaluation Metrics 28
4.2 Result of the GeoWeb Resource Ontology 29
4.3 Graphic User Interface 32
4.4 Evaluation with Artificial Users 33
4.4.1 Analysis of Experiment 1 Results 33
4.4.2 Analysis of Experiment 2 Results 36
4.5 Evaluation with Real Users 40
5. Conclusions and Future Works 43
REFERENCES 44
Appendix A 48
Appendix B 51
Appendix C 54
參考文獻 REFERENCES
[1] G. Mountrakis and A. Stefanidis, “Moving towards Personalized Geospatial Queries,” J. Geogr. Inf. Syst., vol. 03, no. 04, pp. 334–344, 2011, doi: 10.4236/jgis.2011.34031.
[2] M. G. Tait, “Implementing geoportals: Applications of distributed GIS,” Comput. Environ. Urban Syst., 2005, doi: 10.1016/j.compenvurbsys.2004.05.011.
[3] P. Yang, J. Evans, M. Cola, S. Marley, N. Alameh, and M. Bambacus, “The emerging concepts and applications of the spatial web portal,” Photogramm. Eng. Remote Sensing, 2007, doi: 10.14358/PERS.73.6.691.
[4] L. Liu, D. Li, and Z. Shao, “Design and implementation of a geospatial portal,” Geoinformatics 2008 Jt. Conf. GIS Built Environ. Geo-Simulation Virtual GIS Environ., vol. 7143, no. November, p. 71432E, 2008, doi: 10.1117/12.812616.
[5] W. Kuhn, “Geospatial semantics: Why, of what, and how?,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2005, doi: 10.1007/11496168_1.
[6] C. Y. Huang and H. Chang, “GeoWeb Crawler: An extensible and scalable web crawling framework for discovering geospatial web resources,” ISPRS Int. J. Geo-Information, vol. 5, no. 8, 2016, doi: 10.3390/ijgi5080136.
[7] W. Li and C. Yang, “Joint Center for Intelligent Spatial Computing , George Mason University,” Int. Geosci. Remote Sens. Symp., no. Dl, pp. 1278–1281, 2008.
[8] C. Watters and G. Amoudi, “GeoSearcher: GeoSpatial Ranking of Search Engine Results,” Proc. ASIST Annu. Meet., vol. 39, pp. 409–416, 2002, doi: 10.1002/meet.1450390145.
[9] C. Bone, A. Ager, K. Bunzel, and L. Tierney, “A geospatial search engine for discovering multi-format geospatial data across the web,” Int. J. Digit. Earth, vol. 9, no. 1, pp. 47–62, 2016, doi: 10.1080/17538947.2014.966164.
[10] F. R. Gibotti, G. Câmara, and R. A. Nogueira, “Geodiscover - A specialized search engine to discover geospatial data in the Web,” GEOINFO 2005 - 7th Brazilian Symp. GeoInformatics, no. June, 2005.
[11] P. Corti, A. T. Kralidis, and B. Lewis, “Enhancing discovery in spatial data infrastructures using a search engine,” PeerJ Comput. Sci., vol. 2018, no. 5, pp. 1–15, 2018, doi: 10.7717/peerj-cs.152.
[12] W. Li, M. F. Goodchild, and R. Raskin, “Towards geospatial semantic search: Exploiting latent semantic relations in geospatial data,” Int. J. Digit. Earth, vol. 7, no. 1, pp. 17–37, 2014, doi: 10.1080/17538947.2012.674561.
[13] Y. Hu, “Geospatial Semantics,” Compr. Geogr. Inf. Syst., no. 2017, pp. 80–94, 2018, doi: 10.1016/b978-0-12-409548-9.09597-x.
[14] S. V. Malthankar and S. Kolte, “Client Side Privacy Protection Using Personalized Web Search,” Procedia Comput. Sci., vol. 79, pp. 1029–1035, 2016, doi: 10.1016/j.procs.2016.03.130.
[15] W. Li, C. Yanga, and C. Yang, “An active crawler for discovering geospatial Web services and their distribution pattern - A case study of OGC Web Map Service,” Int. J. Geogr. Inf. Sci., 2010, doi: 10.1080/13658810903514172.
[16] S. Patil, S. Bhattacharjee, and S. K. Ghosh, “A spatial web crawler for discovering geo-servers and semantic referencing with spatial features,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, doi: 10.1007/978-3-319-04483-5_7.
[17] J. T. Sample et al., “Enhancing the US Navy’s GIDB portal with web services,” IEEE Internet Comput., 2006, doi: 10.1109/MIC.2006.96.
[18] A. Schutzberg, “Skylab Mobilesystems Crawls the Web for Web Map Servies,” in OGC User 8: 1–3, 2006.
[19] Z. Li, C. P. Yang, H. Wu, W. Li, and L. Miao, “An optimized framework for seamlessly integrating OGC web services to support geospatial sciences,” Int. J. Geogr. Inf. Sci., 2011, doi: 10.1080/13658816.2010.484811.
[20] P. Agarwal, “Ontological considerations in GIScience,” International Journal of Geographical Information Science. 2005, doi: 10.1080/13658810500032321.
[21] D. Mark, B. Smith, M. Egenhofer, and S. Hirtle, “UCGIS Emerging Research Theme : Ontological Foundations for Geographic Information Science,” Res. Challenges Geogr. Inf. Sci., 2004.
[22] M. J. Egenhofer and D. M. Mark, “Naive geography,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1995, doi: 10.1007/3-540-60392-1_1.
[23] R. G. Golledge, “The nature of geographic knowledge,” Annals of the Association of American Geographers. 2002, doi: 10.1111/1467-8306.00276.
[24] G. H. Cablitz, “Geographical categories: An ontological investigation,” Int. J. Geogr. Inf. Sci., vol. 15, no. 7, pp. 591–612, 2001, doi: 10.1080/13658810110061199.
[25] Y. Bishr, “Overcoming the semantic and other barriers to gis interoperability,” Int. J. Geogr. Inf. Sci., 1998, doi: 10.1080/136588198241806.
[26] F. T. Fonseca, M. J. Egenhofer, P. Agouris, and G. Cmara, “Using ontologies for integrated geographic information systems,” Trans. GIS, 2002, doi: 10.1111/1467-9671.00109.
[27] M. F. Goodchild and L. L. Hill, “Introduction to digital gazetteer research,” International Journal of Geographical Information Science. 2008, doi: 10.1080/13658810701850497.
[28] F. Harvey, W. Kuhn, H. Pundt, Y. Bishr, and C. Riedemann, “Semantic interoperability: A central issue for sharing geographic information,” Ann. Reg. Sci., 1999, doi: 10.1007/s001680050102.
[29] C. B. Jones and R. S. Purves, “Geographical information retrieval,” International Journal of Geographical Information Science. 2008, doi: 10.1080/13658810701626343.
[30] Z. Dou, R. Song, and J. R. Wen, “A large-scale evaluation and analysis of personalized search strategies,” in 16th International World Wide Web Conference, WWW2007, 2007, doi: 10.1145/1242572.1242651.
[31] J. Teevan, S. T. Dumais, and E. Horvitz, “Personalizing search via automated analysis of interests and activities,” in SIGIR 2005 - Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2005, doi: 10.1145/1076034.1076111.
[32] S. Gauch, M. Speretta, A. Chandramouli, and A. Micarelli, “User profiles for personalized information access,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 4321 LNCS, pp. 54–89, 2007, doi: 10.1007/978-3-540-72079-9_2.
[33] I. Horrocks, “Ontologies and the semantic web,” Commun. ACM, vol. 51, no. 12, pp. 58–67, 2008, doi: 10.1145/1409360.1409377.
[34] D. Brickley and R. V. Guha, “RDF Vocabulary Description Language 1.0: RDF Schema, W3C Recommendation 10 February 2004,” W3C, 2004. .
[35] S. Hitzler, P., Krotzsch, M., & Rudolph, Foundations of semantic web technologies. CRC Press, 2009.
[36] P. Bellini, P. Nesi, and G. Pantaleo, “Benchmarking RDF stores for smart city services,” in Proceedings - 2015 IEEE International Conference on Smart City, SmartCity 2015, Held Jointly with 8th IEEE International Conference on Social Computing and Networking, SocialCom 2015, 5th IEEE International Conference on Sustainable Computing and Communications, SustainCom 2015, 2015 International Conference on Big Data Intelligence and Computing, DataCom 2015, 5th International Symposium on Cloud and Service Computing, SC2 2015, 2015, doi: 10.1109/SmartCity.2015.45.
[37] J. Kaur and P. Kaur Buttar, “A Systematic Review on Stopword Removal Algorithms,” Int. J. Futur. Revolut. Comput. Sci. Commun. Eng., no. April, pp. 207–210, 2018, [Online]. Available: http://www.ijfrcsce.org.
[38] D. D. Palmer, “Tokenisation and Sentence Segmentation,” Handb. Nat. Lang. Process., pp. 11–35, 2000.
[39] P. A. Chirita, W. Nejdl, R. Paiu, and C. Kohlschütter, “Using ODP metadata to personalize search,” in SIGIR 2005 - Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2005, doi: 10.1145/1076034.1076067.
[40] X. Jiang and A. H. Tan, “Learning and inferencing in user ontology for personalized Semantic Web search,” Inf. Sci. (Ny)., vol. 179, no. 16, pp. 2794–2808, 2009, doi: 10.1016/j.ins.2009.04.005.
[41] G. Salton and C. S. Yang, “On the specification of term values in automatic indexing,” Journal of Documentation. 1973, doi: 10.1108/eb026562.
[42] S. Shekhar and H. Xiong, “Inverse Distance Weighting,” in Encyclopedia of GIS, 2008.
[43] J. Han, M. Kamber, and J. Pei, “Getting to Know Your Data,” in Data Mining, 2012.
[44] Y. Wang, L. Wang, Y. Li, D. He, W. Chen, and T. Y. Liu, “A theoretical analysis of NDCG ranking measures,” in Journal of Machine Learning Research, 2013.
指導教授 黃智遠(Chih-Yuan Huang) 審核日期 2020-7-29
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明