WebTables: exploring the power of tables on the web
Proceedings of the VLDB Endowment
Supporting the automatic construction of entity aware search engines
Proceedings of the 10th ACM workshop on Web information and data management
Probabilistic databases: diamonds in the dirt
Communications of the ACM - Barbara Liskov: ACM's A.M. Turing Award Winner
Open information extraction from the web
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Redundancy-driven web data extraction and integration
Procceedings of the 13th International Workshop on the Web and Databases
Probabilistic models to reconcile complex data from inaccurate data sources
CAiSE'10 Proceedings of the 22nd international conference on Advanced information systems engineering
Global detection of complex copying relationships between sources
Proceedings of the VLDB Endowment
Towards discovering conceptual models behind web sites
ER'12 Proceedings of the 31st international conference on Conceptual Modeling
| Hi-index | 0.00 |
A relevant number of web sites publish structured data about recognizable concepts (such as stock quotes, movies, restau- rants, etc.). There is a great chance to create applications that rely on a huge amount of data taken from the Web. We present an automatic and domain independent system that performs all the steps required to benefit from these data: it discovers data intensive web sites containing information about an entity of interest, extracts and integrate the published data, and finally performs a probabilistic analysis to characterize the impreciseness of the data and the accuracy of the sources. The results of the processing can be used to populate a probabilistic database.