A New Approach to Discover Periodic Frequent Patterns | Zendy

K. Duraiswamy | Zendy; B. Jayanthi | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

A New Approach to Discover Periodic Frequent Patterns

Author(s) -

K. Duraiswamy,

B. Jayanthi

Publication year - 2011

Publication title -

computer and information science

Language(s) - English

Resource type - Journals

eISSN - 1913-8997

pISSN - 1913-8989

DOI - 10.5539/cis.v4n2p75

Subject(s) - computer science , database transaction , data mining , timestamp , period (music) , set (abstract data type) , tree (set theory) , database , mathematics , programming language , mathematical analysis , physics , computer security , acoustics

Mining Frequent Patterns in transaction database TD has been studied extensively in data mining research. However, most of the existing frequent pattern mining algorithm does not consider the time stamps associated with the transactions. Temporal periodicity of pattern appearance can be regarded as an important criterion for measuring the interestingness of frequent patterns in several applications. In this paper, we extend the existing frequent pattern mining framework to take into account the time stamp as periodicity i.e., the time stamp from the month January to June is as First Period and from July to December as Second Period , and discover frequent patterns for each period. An efficient tree based data structure called periodic-frequent pattern tree that captures the database TD in a highly compact manner and enables a pattern growth mining techniques to generate the complete set of Periodic-Frequent patterns. Example illustrating the proposed approach is given. The characteristics of the algorithm are discussed.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research