Results 41 to 50 of about 10,877 (201)
Personalized and Explainable Aspect‐Based Recommendation Using Latent Opinion Groups
ABSTRACT The problem of explainable recommendation—supporting the recommendation of a product or service with an explanation of why the item is a good choice for the user—is attracting substantial research attention recently. Recommendations associated with an explanation of how the aspects of the chosen item may meet the needs and preferences of the ...
Maryam Mirzaei +2 more
wiley +1 more source
AbstrakAlgoritma yang umum digunakan dalam proses pencarian frequent itemset (data yang paling sering muncul) adalah Apriori. Tetapi Algoritma Apriori mempunyai memiliki kekurangan yaitu membutuhkan waktu yang lama dalam proses pencarian frequent itemset.
Wirdah Choiriah
doaj +3 more sources
Parallel Mining Algorithm for the Enumeration Space of Closed High Utility Itemsets
To address the issues of result redundancy and time overhead in high-dimensional data environments, a closed high utility itemset mining algorithm, SpCHUIM (Closed High Utility Itemsets Mining on Spark), is proposed.
LI Chengyan, SUN Anqi, LIU Songlin
doaj +1 more source
Critical Review for One‐Class Classification: Recent Advances and Reality Behind Them
This review presents a new taxonomy to summarize one‐class classification (OCC) algorithms and their applications. The main argument is that OCC should not learn multiple classes. The paper highlights common violations of OCC involving multiple classes.
Toshitaka Hayashi +3 more
wiley +1 more source
Mining interesting itemsets [PDF]
Data mining aims to discover knowledge in large databases. The desired knowledge, normally represented as patterns, are deemed interesting if they benefit some applications. Therefore, the objective of data mining can be translated to finding interesting patterns from observational data.
openaire +2 more sources
TUB-HAUPM: Tighter Upper Bound for Mining High Average-Utility Patterns
High-utility itemset mining (HUIM) has been gaining popularity in the field of data mining. Frequent itemset mining used to be the main tool to reveal high-frequency patterns but failed to consider the concept of profit.
Jimmy Ming-Tai Wu +3 more
doaj +1 more source
A Fast Minimal Infrequent Itemset Mining Algorithm [PDF]
A novel fast algorithm for finding quasi identifiers in large datasets is presented. Performance measurements on a broad range of datasets demonstrate substantial reductions in run-time relative to the state of the art and the scalability of the ...
Demchuk, Kostyantyn, Leith, Douglas J.
core +1 more source
An Improved Apriori Algorithm for Association Rules
There are several mining algorithms of association rules. One of the most popular algorithms is Apriori that is used to extract frequent itemsets from large database and getting the association rule for discovering the knowledge. Based on this algorithm,
Al-Maolegi, Mohammed, Arkok, Bassam
core +1 more source
Objective 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.
Yuyan Shen +8 more
wiley +1 more source
We build a new, open‐source global copper deposit dataset (GCDD), facilitating AI‐driven data analysis for exploration targeting and improving our understanding of copper mineralizing systems and their mappable expressions. The GCDD hosts information about 1483 copper deposits worldwide, capturing key deposit attributes such as location, genetic type ...
Bin Wang +2 more
wiley +1 more source

