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Consistently handling geographical user data: merging of coreferent POIs

Guy De Tré (UGent) and Antoon Bronselaer (UGent)
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Abstract
In the context of geographic information systems (GIS), points of interest (POIs) are descriptions that denote geographical locations which might be of interest for some user purposes. Examples are nice views, historical buildings, good restaurants, recreation areas, etc. Because information gathering with respect to POIs is usually a resource consuming task, the user community is often involved in this task. In general, POI data that originates from different sources (or users) is vulnerable to imperfections. Different POIs referring to, or describing the same physical geographical location might exist. Such POIs are said to be coreferent POIs. Coreferent POIs must be avoided as they could introduce uncertainty in the data and blemish the database. In this paper, a novel soft computing technique for the (semi-)automatic detection and merging of coreferent POIs is presented. Hereby the focus is on the aspects of the merging technique. Fuzzy set and possibility theory are used to cope with the uncertainties in the data. An illustrative example is provided.
Keywords
GIS, POIs, duplicate detection, soft computing., duplicate merging

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Chicago
De Tré, Guy, and Antoon Bronselaer. 2010. “Consistently Handling Geographical User Data: Merging of Coreferent POIs.” In North American Fuzzy Information Processing Society, 2010 Annual Meeting, 117–122. New York, NY, USA: IEEE.
APA
De Tré, G., & Bronselaer, A. (2010). Consistently handling geographical user data: merging of coreferent POIs. North American Fuzzy Information Processing Society, 2010 Annual meeting (pp. 117–122). Presented at the 2010 Annual meeting of the North American Fuzzy Information Processing Society (NAFIPS 2010), New York, NY, USA: IEEE.
Vancouver
1.
De Tré G, Bronselaer A. Consistently handling geographical user data: merging of coreferent POIs. North American Fuzzy Information Processing Society, 2010 Annual meeting. New York, NY, USA: IEEE; 2010. p. 117–22.
MLA
De Tré, Guy, and Antoon Bronselaer. “Consistently Handling Geographical User Data: Merging of Coreferent POIs.” North American Fuzzy Information Processing Society, 2010 Annual Meeting. New York, NY, USA: IEEE, 2010. 117–122. Print.
@inproceedings{1016654,
  abstract     = {In the context of geographic information systems (GIS), points of interest (POIs) are descriptions that denote geographical locations which might be of interest for some user purposes. Examples are nice views, historical buildings, good restaurants, recreation areas, etc. Because information gathering with respect to POIs is usually a resource consuming task, the user community is often involved in this task. In general, POI data that originates from different sources (or users) is vulnerable to imperfections. Different POIs referring to, or describing the same physical geographical location might exist. Such POIs are said to be coreferent POIs. Coreferent POIs must be avoided as they could introduce uncertainty in the data and blemish the database. In this paper, a novel soft computing technique for the (semi-)automatic detection and merging of coreferent POIs is presented. Hereby the focus is on the aspects of the merging technique. Fuzzy set and possibility theory are used to cope with the uncertainties in the data. An illustrative example is provided.},
  author       = {De Tr{\'e}, Guy and Bronselaer, Antoon},
  booktitle    = {North American Fuzzy Information Processing Society, 2010 Annual meeting},
  isbn         = {9781424478576},
  keyword      = {GIS,POIs,duplicate detection,soft computing.,duplicate merging},
  language     = {eng},
  location     = {Toronto, ON, Canada},
  pages        = {117--122},
  publisher    = {IEEE},
  title        = {Consistently handling geographical user data: merging of coreferent POIs},
  year         = {2010},
}