Volume 8, Issue 3, June 2015, Pages 517 - 529
Modified GUIDE (LM) algorithm for mining maximal high utility patterns from data streams
- Chiranjeevi Manike, Hari Om
- Corresponding Author
- Chiranjeevi Manike
Available Online 1 June 2015.
- https://doi.org/10.1080/18756891.2015.1023589How to use a DOI?
- High utility patterns, Data mining, Maximal Patterns, Anti-monotone property, Transaction projection
- High utility pattern mining is an emerging research topic in the data mining field. Unlike frequent pattern mining, high utility pattern mining deals with non-binary databases, in which the information about purchased quantities of items is maintained. Due to the non-existence of anti-monotone property among the utilities of itemsets, utility mining becomes a big challenge. Moreover, discovering useful patterns from the huge number of potential patterns is a mining bottleneck. However, the compact (Closed and Maximal) high utility pattern mining moderately lessens the number of patterns, but it does not solve it. Recently, an efficient framework called GUIDE, was proposed in the literature to address this issue. Though, GUIDE effectively reduced the number of high utility patterns, yet the quality of few mined patterns and their utilities are not exact. In view of this, we propose a modified MGUIDE algorithm to improve the quality and determine exact utilities of maximal patterns.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Chiranjeevi Manike AU - Hari Om PY - 2015 DA - 2015/06 TI - Modified GUIDE (LM) algorithm for mining maximal high utility patterns from data streams JO - International Journal of Computational Intelligence Systems SP - 517 EP - 529 VL - 8 IS - 3 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2015.1023589 DO - https://doi.org/10.1080/18756891.2015.1023589 ID - Manike2015 ER -