Difference between revisions of "Entity Summary"
From Knoesis wiki
Line 128: | Line 128: | ||
| 0.5333 | | 0.5333 | ||
| 0.5428 | | 0.5428 | ||
− | |+ align="bottom" | Table 4. Comparison between Google and Sindice search APIs for a small random sample of entities (5 entities) | + | |+ align="bottom" | Table 4. Comparison between Google and Sindice search APIs for a small random sample of entities (5 entities). |
|} | |} | ||
=== Dataset === | === Dataset === | ||
Evauation data is available for download [http://knoesis.wright.edu/researchers/kalpa/faces_evaluation.zip download] | Evauation data is available for download [http://knoesis.wright.edu/researchers/kalpa/faces_evaluation.zip download] |
Revision as of 18:38, 14 May 2014
Check back on Friday May 16th 2014 for more details...
Creating Faceted (divesified) Entity Summaries
Creating entity summaries has been of contemporary interest in the Semantic Web community in the recet past. In our approach called FACES: FACed Entity Summaries, we are interested in generating diversified and user friendly summaries.
Evaluation
System | k = 5 | FACES % ↑ | k = 10 | FACES % ↑ | time/entity in seconds |
---|---|---|---|---|---|
FACES | 1.4314 | NA | 4.3350 | NA | 0.76 sec. |
RELIN | 0.4981 | 187 % | 2.5188 | 72 % | 10.96 sec. |
RELINM | 0.6008 | 138 % | 3.0906 | 40 % | 11.08 sec. |
SUMMARUM | 1.2249 | 17 % | 3.4207 | 27 % | NA |
Ideal summ agreement | 1.9168 | 4.6415 |
System | k = 5 | FACES %↑ | k = 10 | FACES %↑ |
---|---|---|---|---|
FACES | 1.8649 | NA | 5.6931 | NA |
RELIN | 0.7339 | 154 % | 3.3993 | 69 % |
RELINM | 0.8695 | 114 % | 4.1551 | 37 % |
SUMMARUM | 1.6484 | 13 % | 4.4919 | 27 % |
Ideal summ agreement | 2.3194 | 5.6228 |
Experiment | FACES % | RELINM % | SUMMARUM % |
---|---|---|---|
Experiment 1 | 84 % | 16 % | NA |
Experiment 2 | 54 % | 16 % | 30 % |
k = 5 | k = 10 | ||
---|---|---|---|
Google search API | Sindice seach API | Google search API | Sindice search API |
3.5 | 3.4 | 0.5333 | 0.5428 |
Dataset
Evauation data is available for download download