Results 11 to 20 of about 2,316 (204)
Behavior Decoding Delineates Seizure Microfeatures and Associated Sudden Death Risks in Mouse Models of Epilepsy. [PDF]
Ann NeurolObjective Behavior and motor manifestations are distinctive yet often overlooked features of epileptic seizures. Seizures can result in transient disruptions in motor control, often organized into specific behavioral sequences that can inform seizure types, onset zones, and outcomes.
Shen Y +8 more
europepmc +2 more sources
Mining Correlated High Utility Itemsets in One Phase
IEEE Access, 2020 High-utility itemset mining (HUIM) in transaction databases has been extensively studied to discover interesting itemsets from users' purchase behaviors. With this, business managers can adjust their sale strategies appropriately to increase profit. HUIM
Bay Vo +8 more
doaj +1 more source
Efficient chain structure for high-utility sequential pattern mining [PDF]
, 2020 High-utility sequential pattern mining (HUSPM) is an emerging topic in data mining, which considers both utility and sequence factors to derive the set of high-utility sequential patterns (HUSPs) from the quantitative databases.
Djenouri, Youcef +4 more
core +4 more sources
A Reinduction-Based Approach for Efficient High Utility Itemset Mining from Incremental Datasets
Data Science and Engineering, 2023 High utility itemset mining is a crucial research area that focuses on identifying combinations of itemsets from databases that possess a utility value higher than a user-specified threshold.
Pushp Sra, Satish Chand
doaj +1 more source
EAHUIM: Enhanced Absolute High Utility Itemset Miner for Big Data
International Journal of Information Management Data Insights, 2022 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
A single‐phase algorithm for mining high utility itemsets using compressed tree structures
ETRI Journal, 2021 Mining high utility itemsets (HUIs) from transaction databases considers such factors as the unit profit and quantity of purchased items. Two‐phase tree‐based algorithms transform a database into compressed tree structures and generate candidate patterns
Anup Bhat B, Harish SV, Geetha M
doaj +1 more source
Closed High Utility Pattern Mining over Data Stream Based on Projection in the Window
Taiyuan Ligong Daxue xuebao, 2022 A fast and effective algorithm EFIM_Closed_DS was proposed to mine closed and high utility itemsets in the data stream environment. The algorithm is based on the projection technology in the window, and the database projection technology and transaction ...
Muhang LI +4 more
doaj +1 more source
Mining High Utility Itemsets with Regular Occurrence
Journal of ICT Research and Applications, 2016 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
Top ‘N’ Variant Random Forest Model for High Utility Itemsets Recommendation [PDF]
EAI Endorsed Transactions on Energy Web, 2021 High-utility based itemset mining is the advancement of recurrent pattern mining that discovers occurrence of frequent transactions from a huge database.
Pazhaniraja N +3 more
doaj +1 more source