Geography Reference
In-Depth Information
a
b
Statue
Statue
Grand Hotel
Grand Hotel
Opera
Opera
Fig. 5.1 Computing a landmark: ( a ) identifying geographic objects that may serve as a landmark
in principle; ( b ) selecting the most suited landmark for a specific situation
in Fig. 5.1 b , in order to describe the marketplace when coming from the south,
selecting a landmark candidate that is visible early on is a sensible choice; here, this
may be the church.
We term these steps landmark identification and landmark integration , respec-
tively. They are important steps in computing a landmark. However, they are often
performed by different algorithms and research addresses either one or the other.
Accordingly, the next section will present approaches to identifying landmarks.
Section 5.3 then will illustrate approaches to integrating landmarks. Section 5.4
will compare the approaches to identification and integration of landmarks, which
will lead to a criticism of existing approaches, presented in Sect. 5.5 . That
section will also argue for some extensions and alternative approaches, respectively,
to circumvent some of the inherent drawbacks that come with the current approaches
to computing landmarks. To a large extent it seems these drawbacks are mainly
responsible for why landmarks are not used (more) in today's location-based
services.
5.2
Landmark Identification
The aim of landmark identification is to find all geographic objects in a given region
that may serve as a landmark in principle . To achieve this, for each object its salience
for people needs to be determined. Salience can either be computed or inferred from
how these objects are referred to in some data source. In other words, algorithms for
landmark identification either use attribute data of geographic objects (Sect. 5.2.1 )
or they mine other document sources to determine an object's salience by the way
(and number of times) documents refer to that object (Sect. 5.2.2 ) .
 
 
 
 
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