Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Wareesa Sharif"'
Autor:
Sarah Abdulkarem Al-shalif, Norhalina Senan, Faisal Saeed, Wad Ghaban, Noraini Ibrahim, Muhammad Aamir, Wareesa Sharif
Publikováno v:
PeerJ Computer Science, Vol 10, p e2084 (2024)
Feature selection (FS) is a critical step in many data science-based applications, especially in text classification, as it includes selecting relevant and important features from an original feature set. This process can improve learning accuracy, s
Externí odkaz:
https://doaj.org/article/0595860f0afd4547b5bf427fade1f504
Autor:
Sarah Abdulkarem Alshalif, Norhalina Senan, Faisal Saeed, Wad Ghaban, Noraini Ibrahim, Muhammad Aamir, Wareesa Sharif
Publikováno v:
IEEE Access, Vol 11, Pp 71739-71755 (2023)
The use of text data with high dimensionality affects classifier performance. Therefore, efficient feature selection (FS) is necessary to reduce dimensionality. In text classification challenges, FS algorithms based on a ranking approach are employed
Externí odkaz:
https://doaj.org/article/3bc75b56ffaa4701a338e242b277d99f
Publikováno v:
Frontiers in Psychology, Vol 13 (2022)
Online product recommendation (OPR) systems have gained prominence in the context of e-commerce over the past years. Despite the increased research on OPR use, less attention has been paid to examining how decision and affective assessment of the OPR
Externí odkaz:
https://doaj.org/article/6089919299d64bab90a1ec158da5e206
Autor:
Urooj Akram, Wareesa Sharif, Mobeen Shahroz, Muhammad Faheem Mushtaq, Daniel Gavilanes Aray, Ernesto Bautista Thompson, Isabel de la Torre Diez, Sirojiddin Djuraev, Imran Ashraf
Publikováno v:
Sensors, Vol 23, Iss 14, p 6379 (2023)
An Internet of Things (IoT) network is prone to many ways of threatening individuals. IoT sensors are lightweight, lack complicated security protocols, and face threats to privacy and confidentiality. Hackers can attack the IoT network and access per
Externí odkaz:
https://doaj.org/article/2a6fa14a834f40758fdae4954f181602
Autor:
Muhammad Zulqarnain, Ahmed Khalaf Zager Alsaedi, Rozaida Ghazali, Muhammad Ghulam Ghouse, Wareesa Sharif, Noor Aida Husaini
Publikováno v:
PeerJ Computer Science, Vol 7, p e570 (2021)
Question classification is one of the essential tasks for automatic question answering implementation in natural language processing (NLP). Recently, there have been several text-mining issues such as text classification, document categorization, web
Externí odkaz:
https://doaj.org/article/fb5a8fe989df4a2b81b781f0d3bb166e
Publikováno v:
Cogent Business & Management, Vol 7, Iss 1 (2020)
This study aims to extend expectation-confirmation model (ECM) of IS continuance based on effort-accuracy model (EAM) for predicting and explaining continuous usage of online product recommendation (OPR) that has been ignored in prior literature. The
Externí odkaz:
https://doaj.org/article/55f6be38a0754b1c8ec4060ae42839b4
Autor:
Maria Ali, Muhammad Nasim Haider, Saima Anwar Lashari, Wareesa Sharif, Abdullah Khan, Dzati Athiar Ramli
Publikováno v:
Procedia Computer Science. 207:3459-3468
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca35febf84a3d77d7fd330298bf21ce0
https://doi.org/10.1016/j.procs.2022.09.404
https://doi.org/10.1016/j.procs.2022.09.404
Autor:
Ainin Sulaiman, Noor Ismawati Jaafar, Muhammad Ashraf, Arslan Ali Raza, Muhammad Salman Shabbir, Yuan He, Ramayah Thurasamy, Mazhar Abbas, Wareesa Sharif
Publikováno v:
Current Psychology. 42:6948-6962
Online product recommendation (OPR) plays critical role in purchasing products, but less attention has been given to examine the differential impact of distinct recommendation sources on customer’s decision beliefs and behaviour. This study investi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::13ba0f92e31bd9a2c618bbb6c896af1c
https://doi.org/10.1007/s12144-021-02119-2
https://doi.org/10.1007/s12144-021-02119-2
Autor:
Wareesa Sharif, Barkat Ali, Abdullah Khan, Kamran ullah, Saima Anwar Lashari, Dzati Athiar Ramli
Publikováno v:
KES
Data classification is one of the most frequently used tasks carried out to label information into predefined classes. The most commonly used models for data classification are Feed Forward Artificial Neural Networks (FFANN), and recurrent neural net
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::afcd01e8e30d8491a8c2edc4b102da37
https://doi.org/10.1016/j.procs.2021.09.078
https://doi.org/10.1016/j.procs.2021.09.078
Autor:
Wareesa Sharif, Arslan Ali Raza, Jamil Ahmad, Muhammad Ashraf, Ramayah Thurasamy, Muhammad Salman Shabbir, Mazhar Abbas
Publikováno v:
Online Information Review. 44:745-766
PurposeThis study examines the role of continuous trust (i.e., a trust that develops over time as a result of continuous usage interactions) in determining customers' intention to continue using online product recommendations (OPRs).Design/methodolog
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::601413aa23c5a5343616b0625fe19d38
https://doi.org/10.1108/oir-05-2018-0156
https://doi.org/10.1108/oir-05-2018-0156