Matches in SemOpenAlex for { <https://semopenalex.org/work/W159322950> ?p ?o ?g. }
Showing items 1 to 80 of
80
with 100 items per page.
- W159322950 endingPage "391" @default.
- W159322950 startingPage "377" @default.
- W159322950 abstract "Periodic-frequent patterns are an important class of regularities that exist in a transactional database. Informally, a frequent pattern is said to be periodic-frequent if it appears at a regular interval specified by the user (i.e., periodically) in a database. A pattern-growth algorithm, called PFP-growth, has been proposed in the literature to discover the patterns. This algorithm constructs a tid-list for a pattern and performs a complete search on the tid-list to determine whether the corresponding pattern is a periodic-frequent or a non-periodic-frequent pattern. In very large databases, the tid-list of a pattern can be very long. As a result, the task of performing a complete search over a pattern’s tid-list can make the pattern mining a computationally expensive process. In this paper, we have made an effort to reduce the computational cost of mining the patterns. In particular, we apply greedy search on a pattern’s tid-list to determine the periodic interestingness of a pattern. The usage of greedy search facilitate us to prune the non-periodic-frequent patterns with a sub-optimal solution, while finds the periodic-frequent patterns with the global optimal solution. Thus, reducing the computational cost of mining the patterns without missing any knowledge pertaining to the periodic-frequent patterns. We introduce two novel pruning techniques, and extend them to improve the performance of PFP-growth. We call the algorithm as PFP-growth++. Experimental results show that PFP-growth++ is runtime efficient and highly scalable as well." @default.
- W159322950 created "2016-06-24" @default.
- W159322950 creator A5056438865 @default.
- W159322950 creator A5064495970 @default.
- W159322950 date "2014-01-01" @default.
- W159322950 modified "2023-10-16" @default.
- W159322950 title "Novel Techniques to Reduce Search Space in Periodic-Frequent Pattern Mining" @default.
- W159322950 cites W128175867 @default.
- W159322950 cites W1574579290 @default.
- W159322950 cites W174333354 @default.
- W159322950 cites W180183775 @default.
- W159322950 cites W2068986562 @default.
- W159322950 cites W2106887953 @default.
- W159322950 cites W90754076 @default.
- W159322950 doi "https://doi.org/10.1007/978-3-319-05813-9_25" @default.
- W159322950 hasPublicationYear "2014" @default.
- W159322950 type Work @default.
- W159322950 sameAs 159322950 @default.
- W159322950 citedByCount "25" @default.
- W159322950 countsByYear W1593229502015 @default.
- W159322950 countsByYear W1593229502016 @default.
- W159322950 countsByYear W1593229502017 @default.
- W159322950 countsByYear W1593229502018 @default.
- W159322950 countsByYear W1593229502019 @default.
- W159322950 countsByYear W1593229502020 @default.
- W159322950 countsByYear W1593229502021 @default.
- W159322950 countsByYear W1593229502022 @default.
- W159322950 countsByYear W1593229502023 @default.
- W159322950 crossrefType "book-chapter" @default.
- W159322950 hasAuthorship W159322950A5056438865 @default.
- W159322950 hasAuthorship W159322950A5064495970 @default.
- W159322950 hasConcept C108010975 @default.
- W159322950 hasConcept C111919701 @default.
- W159322950 hasConcept C11413529 @default.
- W159322950 hasConcept C124101348 @default.
- W159322950 hasConcept C153180895 @default.
- W159322950 hasConcept C154945302 @default.
- W159322950 hasConcept C41008148 @default.
- W159322950 hasConcept C48044578 @default.
- W159322950 hasConcept C51823790 @default.
- W159322950 hasConcept C6557445 @default.
- W159322950 hasConcept C68859911 @default.
- W159322950 hasConcept C77088390 @default.
- W159322950 hasConcept C82691427 @default.
- W159322950 hasConcept C86803240 @default.
- W159322950 hasConcept C98045186 @default.
- W159322950 hasConceptScore W159322950C108010975 @default.
- W159322950 hasConceptScore W159322950C111919701 @default.
- W159322950 hasConceptScore W159322950C11413529 @default.
- W159322950 hasConceptScore W159322950C124101348 @default.
- W159322950 hasConceptScore W159322950C153180895 @default.
- W159322950 hasConceptScore W159322950C154945302 @default.
- W159322950 hasConceptScore W159322950C41008148 @default.
- W159322950 hasConceptScore W159322950C48044578 @default.
- W159322950 hasConceptScore W159322950C51823790 @default.
- W159322950 hasConceptScore W159322950C6557445 @default.
- W159322950 hasConceptScore W159322950C68859911 @default.
- W159322950 hasConceptScore W159322950C77088390 @default.
- W159322950 hasConceptScore W159322950C82691427 @default.
- W159322950 hasConceptScore W159322950C86803240 @default.
- W159322950 hasConceptScore W159322950C98045186 @default.
- W159322950 hasLocation W1593229501 @default.
- W159322950 hasOpenAccess W159322950 @default.
- W159322950 hasPrimaryLocation W1593229501 @default.
- W159322950 hasRelatedWork W1515090254 @default.
- W159322950 hasRelatedWork W1525643724 @default.
- W159322950 hasRelatedWork W2067938758 @default.
- W159322950 hasRelatedWork W2153772697 @default.
- W159322950 hasRelatedWork W2277058918 @default.
- W159322950 hasRelatedWork W2302028273 @default.
- W159322950 hasRelatedWork W2364921833 @default.
- W159322950 hasRelatedWork W2382623646 @default.
- W159322950 hasRelatedWork W2464761573 @default.
- W159322950 hasRelatedWork W3087771547 @default.
- W159322950 isParatext "false" @default.
- W159322950 isRetracted "false" @default.
- W159322950 magId "159322950" @default.
- W159322950 workType "book-chapter" @default.