Results 31 to 40 of about 938,194 (261)
Incremental Mining of High Utility Patterns in One Phase by Absence and Legacy-Based Pruning
Mining high utility patterns in dynamic databases is an important data mining task. While a naive approach is to mine a newly updated database in its entirety, the state-of-the-art mining algorithms all take an incremental approach. However, the existing
Junqiang Liu +5 more
doaj +1 more source
EAHUIM: Enhanced Absolute High Utility Itemset Miner for Big Data
High utility itemset mining (HUIM) is a data mining technique that identifies the itemsets with utility levels exceeding a pre-determined threshold. The factor utility is described as the combination of magnitude and element of significance for an item ...
Vandna Dahiya, Sandeep Dalal
doaj +1 more source
Mining High Utility Itemsets with Regular Occurrence
High utility itemset mining (HUIM) plays an important role in the data mining community and in a wide range of applications. For example, in retail business it is used for finding sets of sold products that give high profit, low cost, etc. These itemsets
Komate Amphawan +3 more
doaj +1 more source
ABSTRACT Background Sickle cell disease (SCD) is a chronic, inherited hemoglobinopathy that requires frequent hospitalization for disease‐related complications. Canadian data on inpatient care is limited. This study compared caregiver‐reported hospital experiences of children with SCD to those with cystic fibrosis (CF), a chronic, autosomal recessive ...
Hailey M. Zwicker +11 more
wiley +1 more source
Towards Target High-Utility Itemsets
Preprint.
Jinbao Miao +4 more
openaire +2 more sources
ABSTRACT Background Children with acute lymphoblastic leukemia (ALL) are at risk of severe outcomes from SARS‐CoV‐2 (SCV2). In the post‐pandemic context, where most children have been infected with SCV2, there are limited data on whether vaccination remains beneficial in children with ALL.
Janna R. Shapiro +11 more
wiley +1 more source
Fast Single Pbase Algoritbm for Utility Mining in Big Data
Most of the latest works on utility mining generates a huge number of candidates in dealing with big data,which suffers from the scalability issue.Some work does not generate candidates,but suffers from the efficiency issue due to lack of strong pruning ...
Junqiang Liu +3 more
doaj +2 more sources
High-utility itemset mining for subadditive monotone utility functions
High-utility Itemset Mining (HUIM) finds itemsets from a transaction database with utility no less than a user-defined threshold where the utility of an itemset is defined as the sum of the item-wise utilities. In this paper, we generalize this notion to utility functions that need not be a simple sum of individual utilities.
Siddharth Dawar +2 more
openaire +2 more sources
ABSTRACT Background An internal tandem duplication in the gene encoding Fms‐like tyrosine kinase 3 (FLT3‐ITD) is associated with high relapse risk and poor prognosis in acute myeloid leukemia (AML) and plays a crucial role in treatment decisions. Measurable residual disease (MRD) analysis of FLT3‐ITD during and after treatment has shown prognostic ...
Sofie Johansson Alm +11 more
wiley +1 more source
ABSTRACT Claudin‐6 has emerged as a promising immunotherapeutic target, yet protein‐level data in atypical teratoid/rhabdoid tumors (AT/RTs) have been inconsistent. We analyzed 36 well‐characterized AT/RT samples and found membranous claudin‐6 protein expression in 58% of cases, with striking enrichment in the molecular subgroup AT/RT‐TYR (100%) and ...
Victoria E. Fincke +4 more
wiley +1 more source

