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|Abstract=Searching for entities is a common user activity on the Web. There is an increasing effort in developing entity search techniques in the research community. Existing approaches are usually based on static measures that do not reflect the time-awareness, which is a factor that should be taken into account in entity search. In this paper, we propose a novel approach to time-aware entity search in DBpedia, which takes into account both popularity and temporality of entities. The experimental results show that our approach can significantly improve the performance of entity search with temporal focus compared with the baselines. | |Abstract=Searching for entities is a common user activity on the Web. There is an increasing effort in developing entity search techniques in the research community. Existing approaches are usually based on static measures that do not reflect the time-awareness, which is a factor that should be taken into account in entity search. In this paper, we propose a novel approach to time-aware entity search in DBpedia, which takes into account both popularity and temporality of entities. The experimental results show that our approach can significantly improve the performance of entity search with temporal focus compared with the baselines. | ||
| + | |Download=Paper eswc2015 zhang.pdf, | ||
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Version vom 19. April 2015, 13:14 Uhr
Time-Aware Entity Search in DBpedia
Time-Aware Entity Search in DBpedia
Published: 2015
Mai
Buchtitel: The Semantic Web: ESWC 2014 Satellite Events
Verlag: to appear
Referierte Veröffentlichung
BibTeX
Kurzfassung
Searching for entities is a common user activity on the Web. There is an increasing effort in developing entity search techniques in the research community. Existing approaches are usually based on static measures that do not reflect the time-awareness, which is a factor that should be taken into account in entity search. In this paper, we propose a novel approach to time-aware entity search in DBpedia, which takes into account both popularity and temporality of entities. The experimental results show that our approach can significantly improve the performance of entity search with temporal focus compared with the baselines.
Download: Media:Paper eswc2015 zhang.pdf