Relevant bibliographies by topics / Geographic Information Retrieval

Academic literature on the topic 'Geographic Information Retrieval'

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Published: 4 June 2021
Last updated: 19 February 2022

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Journal articles on the topic "Geographic Information Retrieval"

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Purves, Ross, and Christopher Jones. "Geographic Information Retrieval." SIGSPATIAL Special 3, no. 2 (July 2011): 2–4. http://dx.doi.org/10.1145/2047296.2047297.

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Cardoso, Nuno. "Evaluating Geographic Information Retrieval." SIGSPATIAL Special 3, no. 2 (July 2011): 46–53. http://dx.doi.org/10.1145/2047296.2047307.

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Purves, Ross, and Chris Jones. "Geographic Information Retrieval (GIR)." Computers, Environment and Urban Systems 30, no. 4 (July 2006): 375–77. http://dx.doi.org/10.1016/j.compenvurbsys.2005.12.001.

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Ahlers, Dirk. "Applying Geographic Information Retrieval." Datenbank-Spektrum 14, no. 1 (January 22, 2014): 39–46. http://dx.doi.org/10.1007/s13222-014-0148-z.

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TODA, Hiroyuki, Norihito YASUDA, Manabu OKUMURA, Yumiko MATSUURA, and Ryoji KATAOKA. "Snippet Generation for Geographic Information Retrieval." Transactions of the Japanese Society for Artificial Intelligence 24 (2009): 494–506. http://dx.doi.org/10.1527/tjsai.24.494.

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Lutz, M., and E. Klien. "Ontology‐based retrieval of geographic information." International Journal of Geographical Information Science 20, no. 3 (March 2006): 233–60. http://dx.doi.org/10.1080/13658810500287107.

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Schockaert, Steven. "Vague regions in Geographic Information Retrieval." SIGSPATIAL Special 3, no. 2 (July 2011): 24–28. http://dx.doi.org/10.1145/2047296.2047302.

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YASUDA, Norihito, and Hiroyuki TODA. "Geographic Information Retrieval for Just Your Surroundings." Transactions of the Japanese Society for Artificial Intelligence 23 (2008): 364–73. http://dx.doi.org/10.1527/tjsai.23.364.

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Leveling, Johannes, and Sven Hartrumpf. "On metonymy recognition for geographic information retrieval." International Journal of Geographical Information Science 22, no. 3 (March 2008): 289–99. http://dx.doi.org/10.1080/13658810701626244.

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Purves, Ross, and Chris Jones. "Workshop on geographic information retrieval, SIGIR 2004." ACM SIGIR Forum 38, no. 2 (December 2004): 53–56. http://dx.doi.org/10.1145/1041394.1041406.

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Dissertations / Theses on the topic "Geographic Information Retrieval"

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Lakey, John Christopher. "HIERARCHICAL GEOGRAPHICAL IDENTIFIERS AS AN INDEXING TECHNIQUE FOR GEOGRAPHIC INFORMATION RETRIEVAL." MSSTATE, 2008. http://sun.library.msstate.edu/ETD-db/theses/available/etd-11062008-195327/.

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Location plays an ever increasing role in modern web-based applications. Many of these applications leverage off-the-shelf search engine technology to provide interactive access to large collections of data. Unfortunately, these commodity search engines do not provide special support for location-based indexing and retrieval. Many applications overcome this constraint by applying geographic bounding boxes in conjunction with range queries. We propose an alternative technique based on geographic identifiers and suggest it will yield faster query evaluation and provide higher search precision. Our experiment compared the two approaches by executing thousands of unique queries on a dataset with 1.8 million records. Based on the quantitative results obtained, our technique yielded drastic performance improvements in both query execution time and precision.
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Overell, Simon E. "Geographic information retrieval : Classification, disambiguation and modelling." Thesis, Imperial College London, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.504918.

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Zhu, Bin, and Hsinchun Chen. "Validating a Geographic Image Retrieval System." Wiley Periodicals, Inc, 2000. http://hdl.handle.net/10150/105934.

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Artificial Intelligence Lab, Department of MIS, University of Arizona
This paper summarizes a prototype geographical image retrieval system that demonstrates how to integrate image processing and information analysis techniques to support large-scale content-based image retrieval. By using an image as its interface, the prototype system addresses a troublesome aspect of traditional retrieval models, which require users to have complete knowledge of the low-level features of an image. In addition we describe an experiment to validate the performance of this image retrieval system against that of human subjects in an effort to address the scarcity of research evaluating performance of an algorithm against that of human beings. The results of the experiment indicate that the system could do as well as human subjects in accomplishing the tasks of similarity analysis and image categorization. We also found that under some circumstances texture features of an image are insufficient to represent a geographic image. We believe, however, that our image retrieval system provides a promising approach to integrating image processing techniques and information retrieval algorithms.
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Rydberg, Christoffer. "Time Efficiency of Information Retrieval with Geographic Filtering." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-172918.

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This study addresses the question of time efficiency of two major models within Information Retrieval (IR): the Extended Boolean Model (EBM) and the Vector Space Model (VSM). Both models use the same weighting scheme, based on term-frequency-inverse document frequency (tf-idf). The VSM uses a cosine score computation to rank the document-query similarity. In the EBM, P-norm scores are used, which ranks documents not just by matching terms, but also by taking the Boolean interconnections between the terms in the query into account. Additionally, this study investigates how documents with a single geographic affiliation can be retrieved based on features such as the location and geometry of the geographic surface. Furthermore, we want to answer how to best integrate this geographic search with the two IR-models previously described. From previous research we conclude that using an index based on Z-Space Filling Curves (Z-SFC) is the best approach for documents containing a single geographic affiliation. When documents are retrieved from the Z-SFC-index, there are no guarantees that the retrieved documents are relevant for the search area. It is, however, guaranteed that only the retrieved documents can be relevant. Furthermore, the ranked output of the IR models gives a great advantage to the geographic search, namely that we can focus on documents with a high relevance. We intersect the results from one of the IR models with the results from the Z-SFC index and sort the resulting list of documents by relevance. At this point we can iterate over the list, check for intersections of each document's geometry and the search geometry, and only retrieve documents whose geometries are relevant for the search. Since the user is only interested in the top results we can stop as soon as a sufficient amount of results have been obtained. The conclusion of this study is that the VSM is an easy-to-implement, time efficient, retrieval model. It is inferior to the EBM in the sense that it is a rather simple bag-of-words model, while the EBM allows to specify term- conjunctions and disjunctions. The geographic search has shown to be time efficient and independent of which of the two IR models that is used. The gap in efficiency between the VSM and the EBM, however, drastically increases as the query gets longer and more results are obtained. Depending on the requirements of the user, the collection size, the length of queries, etc., the benefits of the EBM might outweigh the downside of performance. For search engines with a big document collection and many users, however, it is likely to be too slow.
Den här studien addresserar tidseffektiviteten av två större modeller inom informationssökning: ”Extended Boolean Model” (EBM) och ”Vector Space Model” (VSM) . Båda modellerna använder samma typ av viktningsschema, som bygger på ”term frequency–inverse document frequency“ (tf- idf). I VSM rankas varje dokument, utifrån en söksträng, genom en skalärprodukt av dokumentets och söksträngens vektorrepresentationer. I EBM används såkallade ”p-norm score functions” som rankar dokument, inte bara utifrån matchande termer, utan genom att ta hänsyn till de Booleska sammanbindningar som finns mellan sökorden. Utöver detta undersöker studien hur dokument med en geografisk anknytning kan hämtas baserat på positionen och geometrin av den geografiska ytan. Vidare vill vi besvara hur denna geografiska sökning på bästa sätt kan integreras med de två informationssökningmodellerna. Utifrån tidigare forskning dras slutsatsen att det bästa tillvägagångssättet för dokument med endast en geografisk anknytning är att använda ett index baserat på ”Z-Space Filling Curves” (Z-SFC). När dokument hämtas genom Z-SFC-indexet finns det inga garantier att de hämtade dokumenten är relevanta för sökytan. Det är däremot garanterat att endast dessa dokument kan vara relevanta. Vidare är det rankade utdatat från IR-modellerna till en stor fördel för den geografiska sökningen, nämligen att vi kan fokusera på dokument med hög relevans. Detta görs genom att jämföra resultaten från vald IR-modell med resultaten från Z-SFC-indexet och sortera de matchande dokumenten efter relevans. Därefter kan vi iterera över listan och beräkna vilka dokuments geometrier som skär sökningens geometri. Eftersom användaren endast är intresserad av de högst rankade dokumenten kan vi avbryta när vi har tillräckligt många sökresultat. Slutsatsen av studien är att VSM är enkel att implementera och mycket tidseffektiv jämfört med EBM. Modellen är underlägsen EBM i den mening att det är en ganska enkel ”bag of words”-modell, medan EBM tillåter specificering av konjuktioner och disjunktioner. Den geografiska sökningen har visats vara tidseffektiv och oberoende av vilken av de två IR-modellerna som används.Skillnaden i tidseffektivitet mellan VSM och EBM ökar däremot drastiskt när söksträngen blir längre och fler resultat erhålls. Emellertid, beroende på användarens krav, storleken på dokumentsamlingen, söksträngens längd, etc., kan fördelarna med EBM ibland överväga nackdelen av den lägre prestandan. För sökmotorer med stora dokumentsamlingar och många användare är dock modellen sannolikt för långsam.
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Hu, You-Heng Surveying &amp Spatial Information Systems Faculty of Engineering UNSW. "Development, evaluation and application of a geographic information retrieval system." Publisher:University of New South Wales. Surveying & Spatial Information Systems, 2007. http://handle.unsw.edu.au/1959.4/41754.

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Geographic Information Retrieval (GIR) systems provide users with functionalities of representation, storage, organisation of and access to various types of electronic information resources based on their textual and geographic context. This thesis explores various aspects of the development, evaluation and application of GIR systems. The first study focuses upon the extraction and grounding of geographic information entities. My approach for this study consists of a hierarchical structure-based geographic relationship model that is used to describe connections between geographic information entities, and a supervised machine learning algorithm that is used to resolve ambiguities. The proposed approach has been evaluated on a toponym disambiguation task using a large collection of news articles. The second study details the development and validation of a GIR ranking mechanism. The proposed approach takes advantage of the power of the Genetic Programming (GP) paradigm with the aim of finding an optimal functional form that integrates both textual and geographic similarities between retrieved documents and a given user query. My approach has been validated by applying it to a large collection of geographic metadata documents. The third study addresses the problem of modelling the GIR retrieval process that takes into account both thematic and geographic criteria. Based on the Spreading Activation Network (SAN), the proposed model consists a two-layer associative network that is used to construct a structured search space; a constrained spreading activation algorithm that is used to retrieve and to rank relevant documents; and a geographic knowledge base that is used to provide necessary domain knowledge for network. The retrieval performance of my model has been evaluated using the GeoCLEF 2006 tasks. The fourth study discusses the publishing, browsing and navigation of geographic information on the World Wide Web. Key challenges in designing and implementing of a GIR user interface through which online content can be systematically organised based on their geospatial characteristics, and can be efficiently accessed and interrelated, are addressed. The effectiveness and the usefulness of the system are shown by applying it to a large collection of geo-tagged web pages.
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Paiva, Joao Argemiro de Carvalho. "Topological Equivalence and Similarity in Multi-Representation Geographic Databases." Fogler Library, University of Maine, 1998. http://www.library.umaine.edu/theses/pdf/PaivaJA1998.pdf.

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McFarland, Sean Alan. "Decision making theory with geographic information systems support." CSUSB ScholarWorks, 2008. https://scholarworks.lib.csusb.edu/etd-project/3393.

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Decisions are made with varying degrees of effectiveness and efficiency and are influenced by a myriad of internal and external forces. Decision Support Systems (DSS) software can effectively aid decision making through processing the facts and producing meaningful outputs for use by the person or team in making the final choice. Geographic Information Systems (GIS), a form of DSS, are very effective when locational data are present. This thesis talks about using GIS software in decision making procedures.
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McCurry, David B. "Provenance Tracking in a Commons of Geographic Data." Fogler Library, University of Maine, 2007. http://www.library.umaine.edu/theses/pdf/McCurryDB2007.pdf.

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Fraser, Mark E. "Architecture and methodology for storage, retrieval and presentation of geo-spatial information." [Gainesville, Fla.] : University of Florida, 2001. http://purl.fcla.edu/fcla/etd/UFE0000316.

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Thesis (M.S.)--University of Florida, 2001.
Title from title page of source document. Document formatted into pages; contains xi, 77 p.; also contains graphics. Includes vita. Includes bibliographical references.
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Wang, Wei. "Automated spatiotemporal and semantic information extraction for hazards." Diss., University of Iowa, 2014. https://ir.uiowa.edu/etd/1415.

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This dissertation explores three research topics related to automated spatiotemporal and semantic information extraction about hazard events from Web news reports and other social media. The dissertation makes a unique contribution of bridging geographic information science, geographic information retrieval, and natural language processing. Geographic information retrieval and natural language processing techniques are applied to extract spatiotemporal and semantic information automatically from Web documents, to retrieve information about patterns of hazard events that are not explicitly described in the texts. Chapters 2, 3 and 4 can be regarded as three standalone journal papers. The research topics covered by the three chapters are related to each other, and are presented in a sequential way. Chapter 2 begins with an investigation of methods for automatically extracting spatial and temporal information about hazards from Web news reports. A set of rules is developed to combine the spatial and temporal information contained in the reports based on how this information is presented in text in order to capture the dynamics of hazard events (e.g., changes in event locations, new events occurring) as they occur over space and time. Chapter 3 presents an approach for retrieving semantic information about hazard events using ontologies and semantic gazetteers. With this work, information on the different kinds of events (e.g., impact, response, or recovery events) can be extracted as well as information about hazard events at different levels of detail. Using the methods presented in Chapter 2 and 3, an approach for automatically extracting spatial, temporal, and semantic information from tweets is discussed in Chapter 4. Four different elements of tweets are used for assigning appropriate spatial and temporal information to hazard events in tweets. Since tweets represent shorter, but more current information about hazards and how they are impacting a local area, key information about hazards can be retrieved through extracted spatiotemporal and semantic information from tweets.
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Books on the topic "Geographic Information Retrieval"

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Telecommunications, United States Forest Service Computer Sciences &. National geographic information structure. Washington, D.C: U.S. Dept. of Agriculture, Forest Service, Computer Sciences & Telecommunications, 1991.

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Governments and geographic information. London: Taylor & Francis, 1998.

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Scheider, Simon. Grounding geographic information in perceptual operations. Amsterdam: IOS Press, 2012.

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Payne, Roger L. Geographic Names Information System. Reston, Va: The Survey, 1986.

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Geographic Information Systems Awareness Seminar (1988 Salt Lake City, Utah). Proceedings: Geographic Information Systems Awareness Seminar. Edited by Winn David S, Beverly Roberta E, Moore Glenda W, Marshall Dorothy F, and United States. Forest Service. Intermountain Region. Ogden, Utah?]: U.S. Dept. of Agriculture, Forest Service, Intermountain Region, 1989.

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United States. Bureau of Land Management. Denver Service Center. Geographic information system: [concept document]. [Denver, Colo: Bureau of Land Management, Denver Service Center, 1985.

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Goodchild, Michael. Interoperating Geographic Information Systems. Boston, MA: Springer US, 1999.

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United States. Forest Service. Information Systems. National GIS plan: Geographic information system. Washington, D.C: U.S. Dept. of State, Forest Service, Information Systems, 1988.

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GIS online: Information retrieval, mapping, and the Internet. Santa Fe, NM: OnWord Press, 1997.

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National Bureau of Standards. Representation of geographic point locations for information interchange. Gaithersburg, MD: U.S. Dept. of Commerce/National Bureau of Standards, 1987.

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Book chapters on the topic "Geographic Information Retrieval"

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Shekhar, Shashi, and Hui Xiong. "Geographic Information Retrieval." In Encyclopedia of GIS, 362. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_465.

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Kornai, András. "Evaluating Geographic Information Retrieval." In Accessing Multilingual Information Repositories, 928–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11878773_104.

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Lee, Seungwoo, and Gary Geunbae Lee. "A Bootstrapping Approach for Geographic Named Entity Annotation." In Information Retrieval Technology, 178–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-31871-2_16.

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Cai, Guoray. "GeoVSM: An Integrated Retrieval Model for Geographic Information." In Geographic Information Science, 65–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45799-2_5.

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Li, Maozhen, Sheng Zhou, and Christopher B. Jones. "Multi-agent Systems for Web-Based Map Information Retrieval." In Geographic Information Science, 161–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45799-2_12.

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Larson, Ray R. "Geographic Information Retrieval and Digital Libraries." In Research and Advanced Technology for Digital Libraries, 461–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04346-8_59.

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Henrich, Andreas, and Volker Lüdecke. "Measuring Similarity of Geographic Regions for Geographic Information Retrieval." In Lecture Notes in Computer Science, 781–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00958-7_85.

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Leveling, Johannes, Sven Hartrumpf, and Dirk Veiel. "Using Semantic Networks for Geographic Information Retrieval." In Accessing Multilingual Information Repositories, 977–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11878773_109.

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van Kreveld, Marc, Iris Reinbacher, Avi Arampatzis, and Roelof van Zwol. "Distributed Ranking Methods for Geographic Information Retrieval." In Developments in Spatial Data Handling, 231–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/3-540-26772-7_18.

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Dong, Peixiang, Kuizhi Mei, Ji Zhang, Hao Lei, and Jianping Fan. "Task-Driven Image Retrieval Using Geographic Information." In MultiMedia Modeling, 214–26. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04117-9_20.

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Conference papers on the topic "Geographic Information Retrieval"

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Larson, Ray R., and Patricia Frontiera. "Geographic information retrieval (GIR)." In the 27th annual international conference. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/1008992.1009143.

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Mauro, Noemi, Liliana Ardissono, and Adriano Savoca. "Concept-aware geographic information retrieval." In WI '17: International Conference on Web Intelligence 2017. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3106426.3106498.

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Liu, Wei, Hehe Gu, Chunmin Peng, and Dayu Cheng. "Ontology-based retrieval of geographic information." In 2010 18th International Conference on Geoinformatics. IEEE, 2010. http://dx.doi.org/10.1109/geoinformatics.2010.5567612.

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Toda, Hiroyuki, Norihito Yasuda, Yumiko Matsuura, and Ryoji Kataoka. "Geographic information retrieval to suit immediate surroundings." In the 17th ACM SIGSPATIAL International Conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1653771.1653842.

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Khaled, Rezeg, and Soltani Horia. "A mapping ontology for geographic information retrieval." In 2013 3rd International Symposium ISKO-Maghreb. IEEE, 2013. http://dx.doi.org/10.1109/isko-maghreb.2013.6728107.

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Martins, Bruno, and Pável Calado. "Learning to rank for geographic information retrieval." In the 6th Workshop. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1722080.1722107.

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Kumar, Chandan Pramod. "Relevance and Ranking in Geographic Information Retrieval." In Fourth BCS-IRSG Symposium on Future Directions in Information Access (FDIA 2011). BCS Learning & Development, 2011. http://dx.doi.org/10.14236/ewic/fdia2011.1.

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Zaila, Yisleidy Linares, and Danilo Montesi. "Geographic information extraction, disambiguation and ranking techniques." In GIR '15: 9th Workshop on Geographic Information Retrieval. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2837689.2837695.

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Bartlett, Rebecca. "Local geographic information storing and querying using Elasticsearch." In GIR'19: 13th Workshop on Geographic Information Retrieval. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3371140.3371144.

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Khaled, Rezeg. "Mobile agent based approach for Geographic Information retrieval." In 2014 4th International Symposium ISKO-Maghreb: Concepts and Tools for knowledge Management (ISKO-Maghreb). IEEE, 2014. http://dx.doi.org/10.1109/isko-maghreb.2014.7033462.

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