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A probabilistic relational algebra for the integration of information retrieval and database systems
Open accessAbstract
We present a probabilistic relational algebra (PRA) which is a generalization of standard relational algebra. In PRA, tuples are assigned probabilistic weights giving the probability that a tuple belongs to a relation. Based on intensional semantics, the tuple weights of the result of a PRA expression always conform to the underlying probabilistic model. We also show for which expressions extensional semantics yields the same results. Furthermore, we discuss complexity issues and indicate possibilities for optimization. With regard to databases, the approach allows for representing imprecise attribute values, whereas for information retrieval, probabilistic document indexing and probabilistic search term weighting can be modeled. We introduce the concept of vague predicates which yield probabilistic weights instead of Boolean values, thus allowing for queries with vague selection conditions. With these features, PRA implements uncertainty and vagueness in combination with the relational model.
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Cited by
Efficient query evaluation on probabilistic databases
Dalvi, N., & Suciu, D. (2007) · The VLDB Journal · doi:10.1007/s00778-006-0004-3 · Cited by 962
Green, T. J., Karvounarakis, G., & Tannen, V. (2007) · Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems · doi:10.1145/1265530.1265535 · Cited by 812
ULDBs: databases with uncertainty and lineage
Benjelloun, O., Sarma, A. D., Halevy, A. Y., & Widom, J. (2006) · doi:10.5555/1182635.1164209 · Cited by 447
Working Models for Uncertain Data
Sarma, A. D., Benjelloun, O., Halevy, A., & Widom, J. (2006) · 22nd International Conference on Data Engineering (ICDE'06) · doi:10.1109/icde.2006.174 · Cited by 344
Computing and Maintaining Provenance of Query Result Probabilities in Uncertain Knowledge Graphs
Gaur, G., Dang, A., Bhattacharya, A., & Bedathur, S. (2021) · Proceedings of the 30th ACM International Conference on Information & Knowledge Management · doi:10.1145/3459637.3482330 · Cited by 3
Metadata
- Authors
- Fuhr, N., & Rölleke, T.
- Venue
- ACM Transactions on Information Systems
- Published
- 1997-01
- Volume
- 15
- Issue
- 1
- Pages
- 32-66
- ISSN
- 1046-8188 (ISSN-L)
- 1558-2868
- OpenAlex
- W1992609556
- Cited by
- 396
- References
- 0
- FWCI
- 8.88
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Fuhr, N., & Rölleke, T. (1997). A probabilistic relational algebra for the integration of information retrieval and database systems. ACM Transactions on Information Systems. https://doi.org/10.1145/239041.239045
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