Ray R. Larson
Abstract
At the core of any information retrieval system is its method for ranking results in response to a user's query. Geographic Information Retrieval (GIR) systems have an added complexity for this task since the information to be included in the ranking process goes beyond text and word frequency information to encompass geographic proximity, containment and other spatial operations. The need to combine both geographic and text components into GIR systems has led to some interesting hybrid approaches in addition to the "pure" spatial ranking methods based on spatial similarity. In this short survey I will look at some of the methods that have been reported in the literature and used in GIR evaluations including GeoCLEF and NTCIR GeoTime.
- Leonardo Andrade and Mário J. Silva. Relevance ranking for geographic ir. In Workshop on Geographic Information Retrieval, SIGIR '06, USA, 2006. http://www.geo.unizh.ch/rsp/gir06/index.html.Google Scholar
- M. J. Atallah. A linear time algorithm for the Hausdorff distance between convex polygons. Information Processing Letters, 17:207--209, 1983.Google ScholarCross Ref
- Patricia Frontiera, Ray R. Larson, and John Radke. A comparison of geometric approaches to assessing spatial similarity for GIR. International Journal of Geographical Information Science, 22(3):337--360, 2008. Google ScholarDigital Library
- Fredric Gey, Ray Larson, Noriko Kando, Jorge Machado, and Tetsuya Sakai. NTCIR-GeoTime overview: Evaluating geographic and temporal search. In Proceedings of the NTCIR-8 Workshop, Tokyo, June 2010, pages 0--0, 2010.Google Scholar
- Greg Janée. Spatial similarity functions, 2003. Available online at: http://www.alexandria.ucsb.edu/gjanee/archive/2003/similarity.html.Google Scholar
- Greg Janée and James Frew. Spatial search, ranking, and interoperability. In Workshop on Geographic Information Retrieval, SIGIR04, 29 July 2004, Sheffield, South Yorkshire, UK., 2004.Google Scholar
- Ray R. Larson. Cheshire at GeoCLEF 2008: Text and fusion approaches for GIR. In Evaluating Systems for Multilingual and Multi-modal Information Access: 9th Workshop of the Cross-Language Evaluation Forum: CLEF 2008, pages 830--837. Springer (Lecture Notes in Computer Science LNCS 5706), 2009. Google ScholarDigital Library
- Ray R. Larson and Patricia Frontiera. Spatial ranking methods for geographic information retrieval (GIR). In Research and Advanced Technology for Digital Libraries 8th European Conference, ECDL2005, Proceedings (Springer LNCS 3232), pages 45--56, 2004.Google Scholar
- Thomas Mandl, Paula Carvalho, Giorgio Maria Di Nunzio, Fredric C. Gey, Ray R. Larson, Diana Santos, and Christa Womser-Hacker. GeoCLEF 2008: The CLEF 2008 cross-language geographic information retrieval track overview. In Carol Peters, Thomas Deselaers, and Nicola Ferro et al., editors, Evaluating Systems for Multilingual and Multimodal Information Access, volume 5706 of LNCS, pages 808--821. Springer, 2009. Google Scholar
- Thomas Mandl, Fredric C. Gey, Giorgio Maria Di Nunzio, Nicola Ferro, Ray R. Larson, Mark Sanderson, Diana Santos, Christa Womser-Hacker, and Xing Xie. GeoCLEF 2007: The CLEF 2007 cross-language geographic information retrieval track overview. In Carol Peters, Valentin Jijkoun, and Thomas Mandl et al., editors, Advances in Multilingual and Multimodal Information Retrieval, volume 5152 of LNCS, pages 745--772. Springer, 2008. Google Scholar
- Mor Naaman, Y. J. Song, Andreas Paepcke, and Hector Garcia-Molina. Assigning textual names to sets of geographic coordinates. Computers, Environment and Urban Systems, pages 418--435, 2006.Google Scholar
- Ross Purves, Chris Jones, and Paul Clough. Gir' 10: 6th workshop on geographic information retrieval, 2010. http://www.geo.unizh.ch/rsp/gir10/index.html. Google ScholarCross Ref
- E. Rauch, M. Bukatin, and K. Baker. A confidence-based framework for disambiguating geographic terms. In Proceedings of the HLT-NAACL 2003 workshop on Analysis of geographic references, 31 May 2003, Edmonton Canada, 2003. Google ScholarDigital Library
Index Terms
- Ranking approaches for GIR
Recommendations
Challenges for indexing in GIR
Geographic information retrieval (GIR) has been evaluated in campaigns such as GeoCLEF, GikiP, and GikiCLEF [8, 12, 11]. Surprisingly, most results from these evaluations showed that adding more geographic knowledge typically had little or no effect on ...
GIR experimentation
CLEF'06: Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrievalThe Geographic Information Retrieval (GIR) community has generally accepted the thesis that both thematic and geographic aspects of documents are useful for GIR. This paper describes an experiment exploring this thesis by separately indexing and ...
Geographic information retrieval (GIR) ranking methods for digital libraries
JCDL '04: Proceedings of the 4th ACM/IEEE-CS joint conference on Digital librariesThis demo will presents results from an evaluation of algorithms forranking results by probability of relevance for Geographic Information Retrieval (GIR) applications. We will demonstrate an algorithm for GIR ranking based on logistic regression from ...
Comments