TY  - CONF
AU  - Rezel, R.
AU  - Liang, S.
A2  - 
T1  - SWE-FE: Extending folksonomies to the Sensor Web
T2  - 2010 International Symposium on Collaborative Technologies and Systems (CTS)
PB  - IEEE
C1  - 
PY  - 2010/05
CY  -  
VL  - 
IS  - 
SP  - 349
EP  - 356
UR  - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5478494
DO  - 10.1109/CTS.2010.5478494
KW  - tagging
KW  - taggingsurvey
KW  - sensor
KW  - collaborative
KW  - everyaware
KW  - folksonomy
KW  - toread
L1  - 
SN  - 
N1  - 
N1  - 
AB  - This paper presents SWE-FE: a suite of methods to extend folksonomies to the worldwide Sensor Web in order to tackle the emergent data rich information poor (DRIP) syndrome afflicting most geospatial applications on the Internet. SWE-FE leverages the geospatial information associated with three key components of such collaborative tagging systems: tags, resources and users. Specifically, SWE-FE provides algorithms for: i) suggesting tags for users during the tag input stage; ii) generating tag maps which provides for serendipitous browsing; and iii) personalized searching within the folksonomy. We implement SWE-FE on the GeoCENS Sensor Web platform as a case study for assessing the efficacy of our methods. We outline the evaluation framework that we are currently employing to carry out this assessment.
ER  -

TY  - CONF
AU  - Rezel, R.
AU  - Liang, S.
A2  - 
T1  - SWE-FE: Extending folksonomies to the Sensor Web
T2  - 2010 International Symposium on Collaborative Technologies and Systems (CTS)
PB  - IEEE
C1  - 
PY  - 2010/05
CY  -  
VL  - 
IS  - 
SP  - 349
EP  - 356
UR  - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5478494
DO  - 10.1109/CTS.2010.5478494
KW  - tagging
KW  - sensor
KW  - collaborative
KW  - folksonomy
KW  - toread
KW  - web
L1  - 
SN  - 
N1  - 
N1  - 
AB  - This paper presents SWE-FE: a suite of methods to extend folksonomies to the worldwide Sensor Web in order to tackle the emergent data rich information poor (DRIP) syndrome afflicting most geospatial applications on the Internet. SWE-FE leverages the geospatial information associated with three key components of such collaborative tagging systems: tags, resources and users. Specifically, SWE-FE provides algorithms for: i) suggesting tags for users during the tag input stage; ii) generating tag maps which provides for serendipitous browsing; and iii) personalized searching within the folksonomy. We implement SWE-FE on the GeoCENS Sensor Web platform as a case study for assessing the efficacy of our methods. We outline the evaluation framework that we are currently employing to carry out this assessment.
ER  -