Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Vineet Kumar Sejwal"'
Autor:
Shakir Khan, Mohd Fazil, Vineet Kumar Sejwal, Mohammed Ali Alshara, Reemiah Muneer Alotaibi, Ashraf Kamal, Abdul Rauf Baig
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 7, Pp 4335-4344 (2022)
Online social networks(OSNs) face the challenging problem of hate speech, which should be moderated for the growth of OSNs. The machine learning approaches dominate the existing set of approaches for hate speech detection. In this study, we introduce
Externí odkaz:
https://doaj.org/article/60ea4d1c54b344fa8f2fec6d0c335dca
Autor:
Shakir Khan, Ashraf Kamal, Mohd Fazil, Mohammed Ali Alshara, Vineet Kumar Sejwal, Reemiah Muneer Alotaibi, Abdul Rauf Baig, Salihah Alqahtani
Publikováno v:
IEEE Access, Vol 10, Pp 7881-7894 (2022)
Adversaries and anti-social elements have exploited the rapid proliferation of computing technology and online social media in the form of novel security threats, such as fake profiles, hate speech, social bots, and rumors. The hate speech problem on
Externí odkaz:
https://doaj.org/article/1d97048da32849e983273e8967c4374b
Publikováno v:
IEEE Transactions on Computational Social Systems. :1-12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::200b19c8e74df856e1fc334010bfa576
https://doi.org/10.1109/tcss.2023.3236527
https://doi.org/10.1109/tcss.2023.3236527
Autor:
Muhammad Abulaish, Vineet Kumar Sejwal
Publikováno v:
Multimedia Tools and Applications. 80:7247-7269
An ontology is a formal representation of domain knowledge as a set of concepts and their relationships in structured format. Besides various applications, ontology has been frequently used for the development of movie recommender systems that aim to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::033667a4fac97d784b74c7b15ef8b836
https://doi.org/10.1007/s11042-020-10076-4
https://doi.org/10.1007/s11042-020-10076-4
Publikováno v:
IEEE Access, Vol 8, Pp 158432-158448 (2020)
Linked Open Data (LOD) is an emerging Web technology to store and publish structured data in the form of interlinked knowledgebases like DBpedia, Freebase, Wikidata, and Yago. It uses structured data from multiple domains, and it can be used to conce
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d592ed65e32eabdebc7aeee14bafe08
https://ieeexplore.ieee.org/document/9178790/
https://ieeexplore.ieee.org/document/9178790/
Autor:
Muhammad Abulaish, Vineet Kumar Sejwal
Publikováno v:
International Journal of Advanced Computer Science and Applications. 11
Collaborative Filtering (CF) is one of the most fre-quently used recommendation techniques to design recommender systems that improve accuracy in terms of recommendation, coverage, and rating prediction. Although CF is a well-established and popular
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ad429e1bf5526423ce236a0503167ed
https://doi.org/10.14569/ijacsa.2020.0111070
https://doi.org/10.14569/ijacsa.2020.0111070
Autor:
Vineet Kumar Sejwal, Muhammad Abulaish
Publikováno v:
WIMS
In order to tackle the problem of information overload and effective recommendation based on users' preference, need, and interest a number of research contributions has been made for the development of recommender systems. However, certain challenge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d3747d20fc5551f6cb81eeaf0f11cb28
https://doi.org/10.1145/3326467.3326491
https://doi.org/10.1145/3326467.3326491
Autor:
Vineet Kumar Sejwal, Muhammad Abulaish
Publikováno v:
WIMS
Linked Open Data (LOD) consists of various knowledgebases, such as DBpedia, Yago, and Freebase, and uses structured data as features to conceptualize a domain of interest. During last few years, many researchers have shown how LOD can be utilized in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::575daad842cdf6dae9f8afdd4f53cfc4
https://doi.org/10.1145/3326467.3326489
https://doi.org/10.1145/3326467.3326489