NDLI: Unveiling locations in geo-spatial documents

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Unveiling locations in geo-spatial documents

Content Provider	ACM Digital Library
Author	Chafekar, Deepti Chandra, Umesh Lee, Juong-Sik Ranjan, Gyan
Abstract	Resolving geo-identities of addresses in emerging economies where users rely primarily on short messaging as the means of querying, poses several daunting challenges: lack of proper addressing schemes, non-availability of cartographic information and non-standardized nomenclature of geo-spatial entities such as streets and avenues, to name a few. In this work, we propose a simple and elegant approach to solve this problem for emerging economies. By treating address texts as short documents and exploiting latent proximity information contained in them --- for example, landmark like references, similarity of address texts etc --- we transform the problem of resolving geo-identity to a search problem on short annotated geo-spatial documents, collected through extensive survey of six cities in India. Our solution spans all the phases of building a geo-identity resolution system, even though our emphasis is on the collection and organization of the corpus to facilitate a search engine backend for the task. Through experimentation based on a representative test set collected from the real world, we demonstrate how this approach achieves over 94% accuracy in resolution and an order of magnitude reduction in system state (memory) with nearly zero false-negatives - a significant improvement over the state of the art in emerging markets.
Starting Page	401
Ending Page	404
Page Count	4
File Format	PDF
ISBN	9781450310314
DOI	10.1145/2093973.2094033
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-11-01
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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