Geography Reference
In-Depth Information
integration of the most relevant candidates into the offered service. We discussed
several approaches that allow for identifying landmark candidates, either using
geographic data or less structured data (texts, photographs) as a source. We then
presented approaches that given a set of landmark candidates are able to select those
candidates that are best suited for a specific situation.
We have seen that these two steps are not well integrated in today's existing
approaches and that there are further more serious issues that prevent landmarks
from being widely used in (commercial) applications, most importantly the huge
effort of collecting all the data needed for a useful landmark identification. This led
us to an outlook on some alternative approaches to acquiring this data, namely using
types instead of individuals, or tapping into the power of user-generated content.
The next chapter will now connect human and machine by discussing how
landmarks may enrich the interaction between them—in both directions.
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