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Computing Geo-Spatial Motives from Linked Data for Search-driven Applications
Published on Jul 15, 20151783 Views
The Web of Data puts a vast and ever-increasing amount of information at the disposal of its users. In the era of big data, interpreting and exploiting these information is both a highly active resear
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Chapter list
Computing Geo-Spatial Motives from Linked Data for Search-driven Applications00:00
Unister Group: Multi-brand strategy - 100:12
Unister Group: Multi-brand strategy - 201:10
Unister Group: Multi-brand strategy - 301:37
GeoKnow in a nutshell - 101:58
GeoKnow in a nutshell - 201:58
GeoKnow in a nutshell - 302:17
GeoKnow in a nutshell - 402:41
GeoKnow Consortium03:15
Example - 103:47
Example - 204:27
Example - 304:43
Problem Description - 105:06
Problem Description - 205:34
Problem Description - 306:02
Research Questions - 106:25
Research Questions - 207:35
Research Questions - 308:02
Data Sets (Geo-spatial Entities)08:05
Approach - 109:34
Approach - 210:08
Case Study - 110:10
Case Study - 210:42
Case Study - 311:21
Case Study: Education - 112:09
Case Study: Education - 212:10
Case Study: Education - 312:20
Case Study: Education - 412:33
Training - 112:39
Training - 212:55
Training - 313:32
Experimental Settings - 113:56
Experimental Settings - 214:44
Results - 115:00
Results - 215:37
Conclusion and Future Work - 116:41
Conclusion and Future Work - 217:22
Conclusion and Future Work - 317:34
Conclusion and Future Work - 418:20
Results - 318:42
Conclusion and Future Work - 619:05
Take Away19:58