Minimum threshold determination method based on dataset characteristics in association rule mining
Association rule mining is a technique that is widely used in data mining. This technique is
used to identify interesting relationships between sets of items in a dataset and predict …
used to identify interesting relationships between sets of items in a dataset and predict …
[HTML][HTML] How can we use artificial intelligence for stock recommendation and risk management? A proposed decision support system
RMD Gonzales, CA Hargreaves - International Journal of Information …, 2022 - Elsevier
Background Decision-making in the stock market is convoluted as it requires significant
trading experience and knowledge. Faced with a huge range of stocks, investors in the stock …
trading experience and knowledge. Faced with a huge range of stocks, investors in the stock …
Drug Recommender Systems: A Review of State-of-the-Art Algorithms
TO Omodunbi, GE Alilu… - 2022 5th Information …, 2022 - ieeexplore.ieee.org
Drug Recommender Systems (DRSs) which are information systems that recommend drug
(s) to users based on their symptoms and other factors, have been gaining a lot of research …
(s) to users based on their symptoms and other factors, have been gaining a lot of research …
Multi-criteria recommender system model for lockdown decision of Covid-19
A lockdown is an appropriate method to suppress the spread of COVID-19 in a region.
However, apart from the spread of COVID-19, it also affects various aspects and sectors …
However, apart from the spread of COVID-19, it also affects various aspects and sectors …
Optimization of hijaiyah letter handwriting recognition model based on deep learning
A Rahmatulloh, RI Gunawan… - … in Data Science, E …, 2022 - ieeexplore.ieee.org
Hijaiyah handwriting recognition is a challenging research topic. There have been many
works and research on character recognition from various languages, but the accuracy …
works and research on character recognition from various languages, but the accuracy …
Pruning strategy on adaptive rule model by sorting utility items
The adaptive Rule Model is an association rule development that formulates a minimum
threshold value according to the data characteristics. The formulation process is based on …
threshold value according to the data characteristics. The formulation process is based on …
Rule-ranking method based on item utility in adaptive rule model
Background Decision-making is an important part of most human activities regardless of
their daily activities, profession, or political inclination. Some decisions are relatively simple …
their daily activities, profession, or political inclination. Some decisions are relatively simple …
A hybrid recommender system based on customer behavior and transaction data using generalized sequential pattern algorithm
In the future, the quality of product suggestions in online retailers will influence client
purchasing decisions. Unqualified product suggestions can result in two sorts of errors: false …
purchasing decisions. Unqualified product suggestions can result in two sorts of errors: false …
A recommendation system for personalized daily life services to promote frailty prevention
Frailty is a clinical syndrome that commonly occurs in older adults and characterizes an
intermediate state between robust health and the loss of autonomy. As such, it is crucial to …
intermediate state between robust health and the loss of autonomy. As such, it is crucial to …
A comprehensive survey on recommender system techniques
T Ganesan, RA Jothi… - International Journal of …, 2023 - inderscienceonline.com
The recommender system (RecSys) is a relatively emergent research area in machine
learning that helps users to get personalised products, friends, documents, places and other …
learning that helps users to get personalised products, friends, documents, places and other …