Association mining often produces large collections of association rules that are difficult to understand and put into action. In this paper, we have designed a novel notion of combined patterns to extract useful and actionable knowledge from a large amount of learned rules. We also present definitions of combined patterns, design novel metrics to measure their interestingness and analyze the r...

In this paper we are presenting a new way to disable DDL statements on some specific PL/SQL procedures to a dba user in the Oracle database. Nowadays dba users have access to a lot of data and source code even if they do not have legal permissions to see or modify them. With this method we can disable the ability to execute DDL and DML statements on some specific pl/sql procedures from every Or...

Integrity constraints are rules which should guarantee the integrity of a database. Provided that an adequate mechanism to express them is available, the following question arises: is there any way to populate a database which satisfies the constraints supplied by a designer? i.e., does the database schema, including constraints, admit at least one model in which all classes are non-empty? This...

In [DDL] we defined a class of non-compact polygonal billiards, the infinite step billiards: to a given sequence of non-negative numbers {pn}n∈N, such that pn ց 0, there corresponds a table P := ⋃ n∈N[n, n+ 1]× [0, pn]. In this article, first we generalize the main result of [DDL] to a wider class of examples. That is, a.s. there is a unique escape orbit which belongs to the αand ω-limit of eve...

Undergeneration is a problem that undermines successful parsing of unrestricted texts. A popular solution to this problem is automatic grammar correction (or machine learning of grammar). Broadly speaking, grammar correction approaches can be classiied as being either data-driven, or model-based. Data-driven learners use data-intensive methods to acquire grammar. They typically use grammar form...

We initiate a study comparing effectiveness of the transformed spaces learned by recently proposed supervised, and semisupervised metric learning algorithms to those generated by previously proposed unsupervised dimensionality reduction methods (e.g., PCA). Through a variety of experiments on different realworld datasets, we find IDML-IT, a semisupervised metric learning algorithm to be the mos...