Management of probabilistic data: foundations and challenges
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Efficient aggregation algorithms for probabilistic data
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Query processing over incomplete autonomous databases
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Data integration with uncertainty
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Generating efficient safe query plans for probabilistic databases
Data & Knowledge Engineering
ACM SIGMOD Record
Continuous probabilistic nearest-neighbor queries for uncertain trajectories
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Data integration with uncertainty
The VLDB Journal — The International Journal on Very Large Data Bases
Anonymized data: generation, models, usage
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
The VLDB Journal — The International Journal on Very Large Data Bases
Similarity search on Bregman divergence: towards non-metric indexing
Proceedings of the VLDB Endowment
ETAK: tailoring architectural evolution by (re-)using architectural knowledge
Proceedings of the 2010 ICSE Workshop on Sharing and Reusing Architectural Knowledge
On probabilistic models for uncertain sequential pattern mining
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications: Part I
Mining sequential patterns from probabilistic databases
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part II
Ranking continuous nearest neighbors for uncertain trajectories
The VLDB Journal — The International Journal on Very Large Data Bases
Mining sequential patterns from probabilistic databases by pattern-growth
BNCOD'11 Proceedings of the 28th British national conference on Advances in databases
Efficiently answering probability threshold-based shortest path queries over uncertain graphs
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
PNN query processing on compressed trajectories
Geoinformatica
Models for incomplete and probabilistic information
EDBT'06 Proceedings of the 2006 international conference on Current Trends in Database Technology
Uncertainty in sequential pattern mining
BNCOD'10 Proceedings of the 27th British national conference on Data Security and Security Data
Efficient subgraph similarity search on large probabilistic graph databases
Proceedings of the VLDB Endowment
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Overview: Probabilistic query answering is a fundamental set of techniques that underlies several, very recent database applications: exploratory queries in databases, novel IR-style approaches to data integration, querying information extracted from the Web, queries over sensor networks, data acquisition, querying data sources that violate integrity constraints, controlling information disclosure in data exchange, and reasoning about privacy breaches in data mining. This is a surprisingly diverse range of applications, most of which have either emerged recently, or have seen a recent increased interest, and which all share a common fundamental abstraction: that an item being in the answer to a query is no longer a boolean value, but a probabilistic event. It this authors belief that this is a new paradigm in query answering, whose foundations lie in random graphs, and 0/1-laws in finite model theory. The results from these fields, and their relevance to the probabilistic query answering method, are very little known in the database research community, and the theoretical research papers or books that describe them are not very popular in the systems database research community.