However, when mining a large database, the number of patterns discovered can remain large even after adjusting significance thresholds to eliminate spurious patterns. What is needed, then, is an effective measure to further assist in the interpretation and evaluation step that ranks the ...
Mining dense subgraph patterns in a given graph is a problem of growing importance, owing to the increased availability and importance of social networks between people, computer networks such as the internet, relations between information sources such as the world wide web, similarity networks between...
Interestingness discovery is a process employed in data mining and knowledge discovery to classify the usefulness of patterns. Advertisements Many different patterns such as customer spending and social trends are often discovered in data mining, but the relevance, utility, or usefulness of said patterns...
Interestingness measures for data mining:A survey A survey of interestingness measures for knowledge discovery Selecting the right interestingness measure for association patterns Selecting the right interestingness measure for association patterns On Subjective Measures of Interestingness in Knowledge Discovery ...
A data mining technique usually generates a large amount of patterns and rules. However, most of these patterns are not interesting from a user`s point of view. Beneficial and interesting rules should be selected among those generated rules. This selection process is what we may call a second...
Measuring interestingness in data mining is intended for selecting and ranking patterns according to their potential interest to the user (Geng & Hamilton 2006). Despite studies about the role of the body in cognition, affectivity and emotions, research on interest and interestingness still neglects...
When mining a large database, the number of patterns discovered can easily exceed the capabilities of a human user to identify interesting results. To address this problem, various techniques have been suggested to reduce and/or order th... RJ Hilderman,HJ Hamilton - Springer, Berlin, Heidelberg...
[1], the selection of interesting patterns becomes a serious problem for the human user;we will call this problem the post-mining rule analysis problem.Thus one of the central problems in the,eld of data mining is the development of good mea-sures of interestingness of discovered patterns....
Recently, some researchers have turned their attention to the idea of mining pattern sets rather than individual association rules as another means to deal with redundancy among rules, and ranking patterns using background knowledge (Jaroszewicz and Simovici 2004; Gallo et al. 2007; De Bie et ...
Moreover, we propose a new measure called Imbalance Ratio to gauge the degree of skewness of a data set. We also discuss the efficient computation of interesting patterns of different null-invariant interestingness measures by proposing an algorithm, GAMiner, which complements previous studies. ...