A machine learning approach for stock price prediction
Data mining and machine learning approaches can be incorporated into business
intelligence (BI) systems to help users for decision support in many real-life applications …
intelligence (BI) systems to help users for decision support in many real-life applications …
Sports data mining: predicting results for the college football games
CK Leung, KW Joseph - Procedia Computer Science, 2014 - Elsevier
In many real-life sports games, spectators are interested in predicting the outcomes and
watching the games to verify their predictions. Traditional approaches include subjective …
watching the games to verify their predictions. Traditional approaches include subjective …
Predicting the stock price of frontier markets using machine learning and modified Black–Scholes Option pricing model
R Chowdhury, MRC Mahdy, TN Alam… - Physica A: Statistical …, 2020 - Elsevier
Abstract The Black–Scholes Option pricing model (BSOPM) has long been in use for
valuation of equity options to find the price of stocks. In this work, using BSOPM, we have …
valuation of equity options to find the price of stocks. In this work, using BSOPM, we have …
A data analytic algorithm for managing, querying, and processing uncertain big data in cloud environments
Big data are everywhere as high volumes of varieties of valuable precise and uncertain data
can be easily collected or generated at high velocity in various real-life applications …
can be easily collected or generated at high velocity in various real-life applications …
A new efficient approach for mining uncertain frequent patterns using minimum data structure without false positives
G Lee, U Yun - Future Generation Computer Systems, 2017 - Elsevier
The concept of uncertain pattern mining was recently proposed to fulfill the demand for
processing databases with uncertain data, and various relevant methods have been …
processing databases with uncertain data, and various relevant methods have been …
Parallel social network mining for interesting 'following'patterns
Social networking sites (eg, Facebook, Google+, and Twitter) have become popular for
sharing valuable knowledge and information among social entities (eg, individual users and …
sharing valuable knowledge and information among social entities (eg, individual users and …
Big data analytics of social networks for the discovery of “following” patterns
In the current era of big data, high volumes of valuable data can be easily collected and
generated. Social networks are examples of generating sources of these big data. Users (or …
generated. Social networks are examples of generating sources of these big data. Users (or …
A data science solution for mining interesting patterns from uncertain big data
Nowadays, high volumes of valuable uncertain data can be easily collected or generated at
high velocity in many real-life applications. Mining these uncertain Big data is …
high velocity in many real-life applications. Mining these uncertain Big data is …
A systematic survey on high utility itemset mining
B Rahmati, MK Sohrabi - International Journal of Information …, 2019 - World Scientific
High utility itemset mining considers unit profits and quantities of items in a transaction
database to extract more applicable and more useful association rules. Downward closure …
database to extract more applicable and more useful association rules. Downward closure …
Uncertain frequent pattern mining
CKS Leung - Frequent pattern mining, 2014 - Springer
Frequent pattern mining aims to discover implicit, previously unknown and potentially useful
knowledge—in the form of frequently occurring sets of items—that are embedded in data …
knowledge—in the form of frequently occurring sets of items—that are embedded in data …