Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
A Survey of Web Information Extraction Systems
IEEE Transactions on Knowledge and Data Engineering
Management of probabilistic data: foundations and challenges
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
On the complexity of managing probabilistic XML data
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
ProTDB: probabilistic data in XML
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Matching twigs in probabilistic XML
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Query efficiency in probabilistic XML models
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Data integration with uncertainty
The VLDB Journal — The International Journal on Very Large Data Bases
Probabilistic databases: diamonds in the dirt
Communications of the ACM - Barbara Liskov: ACM's A.M. Turing Award Winner
On the expressiveness of probabilistic XML models
The VLDB Journal — The International Journal on Very Large Data Bases
Query evaluation over probabilistic XML
The VLDB Journal — The International Journal on Very Large Data Bases
Aggregate queries for discrete and continuous probabilistic XML
Proceedings of the 13th International Conference on Database Theory
Proceedings of the 13th International Conference on Database Theory
Querying and updating probabilistic information in XML
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
A probabilistic XML merging tool
Proceedings of the 14th International Conference on Extending Database Technology
Towards a version control model with uncertain data
Proceedings of the 4th workshop on Workshop for Ph.D. students in information & knowledge management
Uncertain version control in open collaborative editing of tree-structured documents
Proceedings of the 2013 ACM symposium on Document engineering
| Hi-index | 0.00 |
We investigate the complexity of performing updates on probabilistic XML data for various classes of probabilistic XML documents of different succinctness. We consider two elementary kinds of updates, insertions and deletions, that are defined with the help of a locator query that specifies the nodes where the update is to be performed. For insertions, two semantics are considered, depending on whether a node is to be inserted once or for every match of the query. We first discuss deterministic updates over probabilistic XML, and then extend the algorithms and complexity bounds to probabilistic updates. In addition to a number of intractability results, our main result is an efficient algorithm for insertions defined with branching-free queries over probabilistic models with local dependencies. Finally, we discuss the problem of updating probabilistic XML databases with continuous probability distributions.