An Improved Fusion-Based Semantic Similarity Measure for Effective Collaborative Filtering Recommendations

Autor: Malak Al-Hassan, Bilal Abu-Salih, Esra’a Alshdaifat, Ahmad Aloqaily, Ali Rodan

Publikováno v: International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-18 (2024)

Abstract Semantic-enhanced recommendation systems are promising approaches to overcome the sparsity and cold-start problems, which are hard to handle using the conventional collaborative filtering (CF) approaches. Further research is needed to effect

Externí odkaz: https://doaj.org/article/a55a95a1f1c146a0b33b9744c3da5a29

Advances in Contextual Action Recognition: Automatic Cheating Detection Using Machine Learning Techniques

Autor: Fairouz Hussein, Ayat Al-Ahmad, Subhieh El-Salhi, Esra’a Alshdaifat, Mo’taz Al-Hami

Publikováno v: Data, Vol 7, Iss 9, p 122 (2022)

Teaching and exam proctoring represent key pillars of the education system. Human proctoring, which involves visually monitoring examinees throughout exams, is an important part of assessing the academic process. The capacity to proctor examinations

Externí odkaz: https://doaj.org/article/99432335845e40799269cab99a1ebaf5

A Novel Scheme for Malicious Nodes Detection in Cloud Markets Based on Fuzzy Logic Technique

Autor: Ayoub Alsarhan, Abdel-Rahman Al-Ghuwairi, Esra'a Alshdaifat, Hasan Idhaim, Omar alkhawaldeh

Publikováno v: International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 03 (2022); pp. 136-150
International Journal of Interactive Mobile Technologies, Vol 16, Iss 03 (2022)

Cloud security vulnerabilities have recently become more prevalent around the world, posing a threat to cloud service providers' (CSPs) ability to respond to client demands. In cloud market, the requests are announced by the client nodes to their CSP

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::deee39751233db3c36e5d5dd5611c5b7
https://doi.org/10.3991/ijim.v16i03.27933

The Effect of Preprocessing Techniques, Applied to Numeric Features, on Classification Algorithms’ Performance

Autor: Fairouz Hussein, Subhieh El-Salhi, Ayoub Alsarhan, Esra’a Alshdaifat, Doa’a Alshdaifat

Publikováno v: Data
Volume 6
Issue 2
Data, Vol 6, Iss 11, p 11 (2021)

It is recognized that the performance of any prediction model is a function of several factors. One of the most significant factors is the adopted preprocessing techniques. In other words, preprocessing is an essential process to generate an effectiv

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c85842868fad499bc2a6c74ca4dab59f

Multithreaded Sliding Window Approach to Improve Exact Pattern Matching Algorithms

Autor: Ala’a Al-shdaifat, Basam Hammo, Mohammad A. M. Abushariah, Esra’a Alshdaifat

Publikováno v: International Journal of Advanced Computer Science and Applications. 8

In this paper an efficient pattern matching ap-proach, based on a multithreading sliding window technique, is proposed to improve the efficiency of the common sequential exact pattern matching algorithms including: (i) Brute Force, (ii) Knuth-Morris-

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::09829444a08366047de70a4c6f53e513
https://doi.org/10.14569/ijacsa.2017.080155