Entity-centric Data Fusion on the Web
Buchtitel: Proceedings of the 28th ACM Conference on Hypertext and Social Media
A lot of current web pages include structured data which can di- rectly be processed and used. Search engines, in particular, gather that structured data and provide question answering capabilities over the integrated data with an entity-centric presentation of the results. Due to the decentralized nature of the web, multiple struc- tured data sources can provide similar information about an entity. But data from di erent sources may involve di erent vocabular- ies and modeling granularities, which makes integration di cult. We present an approach that identi es similar entity-speci c data across sources, independent of the vocabulary and data modeling choices. We apply our method along the scenario of a trustable knowledge panel, conduct experiments in which we identify and process entity data from web sources, and compare the output to a competing system. The results underline the advantages of the presented entity-centric data fusion approach.
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DOI Link: http://dx.doi.org/10.1145/3078714.3078717