Geography Reference
In-Depth Information
(the U in Fig. 7.1 ) , who is the easiest to model. Other factors of the communication
context have not yet been fully addressed, for example, an adaptation to a particular
environment or the time of the day (E).
Another change to the environment, and consequently to the task (T), would be an
adaptation of skeletal descriptions to emergency situations. Again, this is a change
to context that is relatively easy to capture and model. It demands particularly clear
and unambiguous communication. When people are under stress, there is no time
for thinking about what the system may have actually meant.
Adapting descriptions to the prior knowledge of the user would be a desirable
achievement. Such adaptation is fundamental for pragmatic information content,
i.e., communicating only what is relevant. It would prevent your car navigation
system from telling you how to get from your home to the highway in all detail—
something you have likely done hundreds of times before. There is preliminary work
done in that direction as well, most of which assumes that you own the system
that communicates with you. These systems infer your knowledge by tracking your
movements (e.g., [ 9 , 15 ] ). More challenging, but also more interesting, is a scenario
where the system has to figure out the user's prior knowledge by dialog [ 13 ] . Such a
scenario requires flexibility and adaptation, and also strategies of negotiation. This
step gets us finally to (landmark) understanding, which we have argued to be more
difficult than (landmark) producing.
These dialog-based systems will need to understand place descriptions by people
in-situ, using location information as well as keeping track of what has been
mentioned before in the current dialog. But it will require more than this. The system
will have to be capable of mapping the user's understanding of an environment to
its own representation. This means that the systems' internal representations will
need to be created based on the defining elements of human spatial representation—
landmarks.
In the long run these developments will lead to intelligent geospatial systems—
systems as flexible and adaptive as a human communication partner, with re- and
pro-active behavior and constructive communication. Landmarks are the elements
that can tie it all together by structuring both the human and system's representation
of space.
References
1. Agrawala, M., Stolte, C.: Rendering effective route maps: Improving usability through
generalization. In: SIGGRAPH 2001, pp. 241-250. ACM, Los Angeles (2001)
2. Chen, G., Kotz, D.: A survey of context-aware mobile computing research. Technical Report
TR2000-381. Dartmouth College, Hanover (2000)
3. Denis, M.: The description of routes: a cognitive approach to the production of spatial
discourse. Curr. Psychol. Cognit. 16 (4), 409-458 (1997)
4. Dey, A.K.: Understanding and using context. Pers. Ubiquit. Comput. 5 (1), 4-7 (2001)
5. Duckham, M., Winter, S., Robinson, M.: Including landmarks in routing instructions. J.
Location-Based Serv. 4 (1), 28-52 (2010)
 
 
 
 
 
 
 
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