%0 Journal Article
	%A Eiad Yafi and  M. A. Alam and  Ranjit Biswas
	%D 2007
	%J International Journal of Industrial and Manufacturing Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 11, 2007
	%T Development of Subjective Measures of Interestingness: From Unexpectedness to Shocking
	%U https://publications.waset.org/pdf/3488
	%V 11
	%X Knowledge Discovery of Databases (KDD) is the
process of extracting previously unknown but useful and significant
information from large massive volume of databases. Data Mining is
a stage in the entire process of KDD which applies an algorithm to
extract interesting patterns. Usually, such algorithms generate huge
volume of patterns. These patterns have to be evaluated by using
interestingness measures to reflect the user requirements.
Interestingness is defined in different ways, (i) Objective measures
(ii) Subjective measures. Objective measures such as support and
confidence extract meaningful patterns based on the structure of the
patterns, while subjective measures such as unexpectedness and
novelty reflect the user perspective. In this report, we try to brief the
more widely spread and successful subjective measures and propose
a new subjective measure of interestingness, i.e. shocking.
	%P 571 - 573