Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Induction as nonmonotonic inference
Proceedings of the first international conference on Principles of knowledge representation and reasoning
An extended transformation approach to inductive logic programming
ACM Transactions on Computational Logic (TOCL) - Special issue devoted to Robert A. Kowalski
Database System Implementation
Database System Implementation
Relational Data Mining
Discovering Frequent Closed Itemsets for Association Rules
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Multi-relational data mining: an introduction
ACM SIGKDD Explorations Newsletter
Scalability and efficiency in multi-relational data mining
ACM SIGKDD Explorations Newsletter
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Frequent pattern discovery in first-order logic
AI Communications
A Mining Algorithm Using Property Items Extracted from Sampled Examples
Inductive Logic Programming
On mining closed sets in multi-relational data
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Intelligent Data Analysis - Ubiquitous Knowledge Discovery
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We study the problem of mining closed patterns in multirelational databases. Garriga et al. (IJCAI'07) proposed an algorithm RelLCM2 for mining closed patterns (i.e., conjunctions of literals) in multi-relational data, which is an extension of LCM, an efficient enumeration algorithm for frequent closed item-sets mining proposed in the seminal paper by Uno et al. (DS'04). We assume that a database considered contains a special predicate called key (or target), which determines the entities of interest and what is to be counted. We introduce a notion of closed patterns with key (key-closedness for short), where variables in a pattern other than the one in a key predicate are considered to be existentially quantified, and they are linked to a given target object. We then define a closure operation (key-closure) for computing key-closed patterns, and show that the difference between the semantics of key-closed patterns and that of the closed patterns in RelLCM2 implies different properties of the closure operations; in particular, the uniqueness of closure does not hold for key-closure. Nevertheless, we show that we can enumerate key-closed patterns using the technique of ppc-extensions à la LCM, thereby making the enumeration possible without storage space for previously generated patterns. We also propose a literal order designed for mining key-closed patterns, which will require less search space. The correctness of our algorithm is shown, and its computational complexity is discussed. Some preliminary experimental results are also given.