Abstract
Currently, data gathering techniques have increased through which unstructured data creeps in, along with well defined data formats. Mining these data and bringing out useful patterns seems difficult. Various data mining algorithms were put forth for this purpose. The associated patterns generated by the association rule mining algorithms are large in number. Every ARM focuses on positive rule mining and very few literature has focussed on rare_itemsets_mining. The work aims at retrieving the rare itemsets that are of most interest to the user by utilizing various interestingness measures. Both positive and negative itemset mining would be focused in this work.
Highlights
Data Mining has grasped people’s interest due to the availability of a wide range of raw data where useful information is poor
Data Mining cannot work without human effort and it cannot tell the value of information mined for our need
Most of the existing research is on mining positive_association_rules of the pattern P→Q, but we focus on mining negative association rules of the pattern, P→~Q, ~P→Q, ~P→~Q
Summary
Data Mining has grasped people’s interest due to the availability of a wide range of raw data where useful information is poor. The relationship between these meaningful pattern can be identified through a traditional method called Association Rule Mining (ARM). Mined rules have to satisfy some user specified minimum value of support and the confidence Pretty good algorithms such as Apriori, Elcat, FP-growth are available to generate association rules. Most of the existing research is on mining positive_association_rules of the pattern P→Q, but we focus on mining negative association rules of the pattern, P→~Q, ~P→Q, ~P→~Q. This absence of itemsets is considered in our study. Different methods of ARM are discussed which mines frequent and infrequent itemsets from where both positive and negative rules are mined. Various methods that were incorporated to lessen the number of rules generated and number of scans to the database is the main objective discussed in the study
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Engineering & Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
