CSSF-trie structure to mine constraint sequential patterns from progressive database. Issue 4 (1st January 2013)

• Record Type: Journal Article
• Authors: Rao, V. Chandra Shekhar; Sammulal, P.
• Is Part Of: International journal of knowledge engineering and data mining. Volume 2:Issue 4(2013)
• Page Start: 248
• Page End: 265
• Publication Date: 2013-01-01
• Subjects: trie -- sequential pattern mining -- CSSF -- progressive database -- updated CSSF-trie; Knowledge representation (Information theory) -- Periodicals; Data mining -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-2087

Abstract

This paper delineates the purpose of an algorithm for mining constraint sequential patterns from a progressive database. We construct the updated CSSF-trie from the static database with the intention of efficiently capturing the dynamic nature of data addition and deletion into the mining problem. Whenever the database gets updated from the distributed sources, the database may be static, inserted, or deleted. CSSF trie is also updated by including the updated sequence. The updated CSSF-trie is used to mine the progressive CSSF-patterns using the proposed algorithm. Finally, the experimentation is carried out using the synthetic and real life distributed databases that are given to the progressive CSSF-miner using thread environment. The experimental results provide better results in terms of the generated number of sequential patterns, execution time and the memory usage over the existing IncSpan algorithm.