van Keulen, M;
Kaminski, BL;
Matheja, C;
Katoen, J-P;
(2018)
Rule-Based Conditioning of Probabilistic Data.
In: Ciucci, D and Pasi, G and Vantaggi, B, (eds.)
Proceedings of the 12th International Conference on Scalable Uncertainty Management (SUM).
(pp. pp. 290-305).
Springer: Cham, Switzerland.
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Abstract
Data interoperability is a major issue in data management for data science and big data analytics. Probabilistic data integration (PDI) is a specific kind of data integration where extraction and integration problems such as inconsistency and uncertainty are handled by means of a probabilistic data representation. This allows a data integration process with two phases: (1) a quick partial integration where data quality problems are represented as uncertainty in the resulting integrated data, and (2) using the uncertain data and continuously improving its quality as more evidence is gathered. The main contribution of this paper is an iterative approach for incorporating evidence of users in the probabilistically integrated data. Evidence can be specified as hard or soft rules (i.e., rules that are uncertain themselves).
| Type: | Proceedings paper |
|---|---|
| Title: | Rule-Based Conditioning of Probabilistic Data |
| Event: | 12th International Conference on Scalable Uncertainty Management (SUM) |
| Location: | Univ Milano Bicocca, Milan, ITALY |
| Dates: | 03 October 2018 - 05 October 2018 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-3-030-00461-3_20 |
| Publisher version: | https://doi.org/10.1007/978-3-030-00461-3_20 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Science & Technology, Technology, Computer Science, Artificial Intelligence, Computer Science, Theory & Methods, Computer Science, Data cleaning, Data integration, Information extraction, Probabilistic databases, Probabilistic programming |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10089690 |
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