Name
Abstract | ||
|---|---|---|
Proposed a novel model to find partial periodic-frequent patterns in a database.Introduced a measure to find partial periodic-frequent patterns in a database.An efficient pruning technique has been proposed to reduce the computational cost.Described a pattern-growth algorithm to find all partial periodic-frequent patternsExperimental results show that our model is efficient. Time and frequency are two important dimensions to determine the interestingness of a pattern in a database. Periodic-frequent patterns are an important class of regularities that exist in a database with respect to these two dimensions. Current studies on periodic-frequent pattern mining have focused on discovering full periodic-frequent patterns, i.e., finding all frequent patterns that have exhibited complete cyclic repetitions in a database. However, partial periodic-frequent patterns are more common due to the imperfect nature of real-world. This paper proposes a flexible and generic model to find partial periodic-frequent patterns. A new interesting measure, periodic-ratio, has been introduced to determine the periodic interestingness of a frequent pattern by taking into account its proportion of cyclic repetitions in a database. The proposed patterns do not satisfy the anti-monotonic property. A novel pruning technique has been introduced to reduce the search space effectively. A pattern-growth algorithm to find all partial periodic-frequent patterns has also been presented in this paper. Experimental results demonstrate that the proposed model can discover useful information, and the algorithm is efficient. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.jss.2016.11.035 | Journal of Systems and Software |
Keywords | Field | DocType |
Data mining,Knowledge discovery in databases,Pattern mining,Partial periodicity,Algorithms | Data mining,Imperfect,Computer science,Database transaction,Periodic graph (geometry) | Journal |
Volume | Issue | ISSN |
125 | C | 0164-1212 |
Citations | PageRank | References |
6 | 0.44 | 31 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| R. Uday Kiran | 1 | 251 | 25.72 |
| J. N. Venkatesh | 2 | 6 | 0.44 |
| Masashi Toyoda | 3 | 388 | 49.87 |
| Masaru Kitsuregawa | 4 | 3188 | 831.46 |
| P. Krishna Reddy | 5 | 105 | 17.26 |