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PVLDB
2008
120views more  PVLDB 2008»
13 years 3 months ago
On the provenance of non-answers to queries over extracted data
In information extraction, uncertainty is ubiquitous. For this reason, it is useful to provide users querying extracted data with explanations for the answers they receive. Provid...
Jiansheng Huang, Ting Chen, AnHai Doan, Jeffrey F....
DEBU
2010
139views more  DEBU 2010»
13 years 1 months ago
Refining Information Extraction Rules using Data Provenance
Developing high-quality information extraction (IE) rules, or extractors, is an iterative and primarily manual process, extremely time consuming, and error prone. In each iteratio...
Bin Liu 0002, Laura Chiticariu, Vivian Chu, H. V. ...
SIGMOD
2010
ACM
170views Database» more  SIGMOD 2010»
13 years 9 months ago
Querying data provenance
Many advanced data management operations (e.g., incremental maintenance, trust assessment, debugging schema mappings, keyword search over databases, or query answering in probabil...
Grigoris Karvounarakis, Zachary G. Ives, Val Tanne...
ICDT
2001
ACM
124views Database» more  ICDT 2001»
13 years 8 months ago
Why and Where: A Characterization of Data Provenance
Withthe proliferation of database views and curated databases, the issue of data provenance where a piece of data came from and the process by which it arrived in the database is b...
Peter Buneman, Sanjeev Khanna, Wang Chiew Tan
ICDT
2011
ACM
213views Database» more  ICDT 2011»
12 years 7 months ago
On provenance and privacy
Provenance in scientific workflows is a double-edged sword. On the one hand, recording information about the module executions used to produce a data item, as well as the parame...
Susan B. Davidson, Sanjeev Khanna, Sudeepa Roy, Ju...