We study the problem of correcting spelling mistakes in text using memory-based learning techniques and a very large database of token n-gram occurrences in web text as training d...
A wide range of database applications manage information that varies over time. Many of the underlying database schemas of these were designed using one of the several versions of...
This work discusses the problem of generating association rules from a set of transactions in a relational database, taking performance and accuracy of found results as the essent...
We discovered that the set of frequent hybrid sequential patterns obtained by previous researches is incomplete, due to the inapplicability of the Apriori principle. We design and ...
Frequency mining problem comprises the core of several data mining algorithms. Among frequent pattern discovery algorithms, FP-GROWTH employs a unique search strategy using compac...