Entity Summary

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

Table 1. Evaluating the quality of summaries under each setting, % quality improvement (↑) using FACES compared to others for k=5 and k=10, respectively and average time taken per entity.

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

Table 2. Evaluating the quality of correct concepts picked using property overlap under each setting, % quality improvement (↑) using FACES compared to others for k=5 and k=10, respectively.

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

Table 3. Evaluating user preferences for entity summaries using 69 user participants.

Experiment	FACES %	RELINM %	SUMMARUM %
Experiment 1	84 %	16 %	NA
Experiment 2	54 %	16 %	30 %

Dataset

Evauation data is available for download download