Closeness Preference - A new interestingness measure for sequential rules mining
The time-interval between the antecedent and the consequent of a sequential rule can be considered as an important aspect in sequential rules interest. For example, in web logs analysis, the end-user can be interested in predicting the next page that will be visited by an internet surfer based on a history of visited pages. A Closeness Preference measure is proposed to favour the sequential rules with close itemsets based on user time-preference in a post-processing step. We illustrate the interest of the Closeness Preference measure with two real datasets (web logs data and activities of daily living data) for first, a predictive task and second, a descriptive one. Both of them show that Closeness Preference measure is helpful to find small and efficient sets of simple sequential rules. (C) 2013 Elsevier B.V. All rights reserved.
closeness preference interestingness measures sequential rules time-interval user-preference