In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...
We consider the problem of improving the efficiency of query processing on an XML interface of a relational database, for predefined query workloads. The main contribution of this ...
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
A growing mount of available text data are being stored in relational databases, giving rise to an increasing need for the RDBMSs to support effective text retrieval. In this pape...
Decision support applications involve complex queries on very large databases. Since response times should be small, query optimization is critical. Users typically view the data ...
Venky Harinarayan, Anand Rajaraman, Jeffrey D. Ull...