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Multi-Dimensional Scattered Ranking Methods for Geographic Information Retrieval*
 

Summary: Multi-Dimensional Scattered Ranking Methods for
Geographic Information Retrieval*
MARC VAN KREVELD, IRIS REINBACHER, AVI ARAMPATZIS AND ROELOF VAN ZWOL
Institute of Information and Computing Sciences, Utrecht University, The Netherlands
E-mail: {marc, iris, avgerino, roelof }@cs.uu.nl
Received July 21, 2004; Revised November 15, 2004; Accepted November 15, 2004
Abstract
Geographic Information Retrieval is concerned with retrieving documents in response to a spatially related
query. This paper addresses the ranking of documents by both textual and spatial relevance. To this end, we
introduce multi-dimensional scattered ranking, where textually and spatially similar documents are ranked
spread in the list, instead of consecutively. The effect of this is that documents close together in the ranked list
have less redundant information. We present various ranking methods of this type, efficient algorithms to
implement them, and experiments to show the outcome of the methods.
Keywords: geographic information retrieval, relevance ranking, algorithms
1. Introduction
The most common way to return a set of documents obtained from a Web query is by a
ranked list. The search engine attempts to determine which document seems to be the
most relevant to the user and will put it first in the list. In short, every document receives
a score, or distance to the query, and the returned documents are sorted by this score or
distance.

  

Source: Arampatzis, Avi - Department of Electrical and Computer Engineering, Democritus University of Thrace

 

Collections: Computer Technologies and Information Sciences