Zobrazeno 1 - 10 of 38 pro vyhledávání: '"Hamdy M. Mousa"'
1
Akademický článek
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
Autor: Ahmed Latif Yaser, Hamdy M. Mousa, Mahmoud Hussein
Publikováno v: Future Internet, Vol 14, Iss 8, p 240 (2022)
Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security
Externí odkaz: https://doaj.org/article/bad4f3330e5f4380ae8cd647a14ea2e5
Zobrazit plný text záznamu
3
ADPBC: Arabic Dependency Parsing Based Corpora for Information Extraction
Autor: Sally Mohamed, Hamdy M. Mousa, Mahmoud Hussien
Publikováno v: International Journal of Information Technology and Computer Science. 13:54-61
There is a massive amount of different information and data in the World Wide Web, and the number of Arabic users and contents is widely increasing. Information extraction is an essential issue to access and sort the data on the web. In this regard,
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3e41f0236886cd4a6ef04176cdb7716f
https://doi.org/10.5815/ijitcs.2021.01.04
Zobrazit plný text záznamu
5
Improving collaborative filtering using lexicon-based sentiment analysis
Autor: Rouhia Mohammed Sallam, Mahmoud Hussein, Hamdy M. Mousa
Since data is available increasingly on the Internet, efforts are needed to develop and improve recommender systems to produce a list of possible favorite items. In this paper, we expand our work to enhance the accuracy of Arabic collaborative filter
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8352086605204ff3bfda605995f2ea87
https://zenodo.org/record/6774670
Zobrazit plný text záznamu
8
A Novel Scalable and Effective Partitioning Approach for Big Data Reduction
Autor: Hamdy M. Mousa, Mohamed G. Malhat, Mohamed El-Menshawy, Ashraf B. El-Sisi
Publikováno v: IJCI. International Journal of Computers and Information. 6:9-19
The continuous increment of data size makes the traditional instance selection methods ineffective to reduce big training datasets in a single machine. Recent approaches to solving this technical problem partition the training dataset into subsets pr
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2f95a09e50d436a6bbdac3f84f53ff59
https://doi.org/10.21608/ijci.2019.35122
Zobrazit plný text záznamu
9
A Review of Open Information Extraction Techniques
Autor: Hamdy M. Mousa, Sally Ali, Mahmoud Hussien
Publikováno v: IJCI. International Journal of Computers and Information. 6:20-28
Nowadays, massive amount of data flows all the time. Approximately between 20 or 30 percent of these data is text. This data is always organized in semi-structured text, which cannot be used directly. To make use of such huge amounts of textual data,
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::10c4711f6ea6cde22aa4702a31ebe7d9
https://doi.org/10.21608/ijci.2019.35099
Zobrazit plný text záznamu
10
E-PROBCONS: Enhanced PROBCONS for Multiple Sequence Alignment
Autor: Eman M. Mohamed, Hamdy M. Mousa, Arabi Keshk
Publikováno v: IJCI. International Journal of Computers and Information.
— the perfect alignment between three or more sequences of protein, RNA or DNA is a very difficult task in Bioinformatics. There are many techniques for alignment of multiple sequences. Many techniques enlarge speed and do not have a concern with t
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4c31b842d442d58898d274ac563e4386
https://doi.org/10.21608/ijci.2020.15523.1002
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje