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    Wyświetlanie 1-3 z 3
    Tytuł:
    Search engine optimization: a review
    Autorzy:
    Almukhtar, Firas
    Mahmoodd, Nawzad
    Kareem, Shahab
    Powiązania:
    https://bibliotekanauki.pl/articles/1837798.pdf
    Data publikacji:
    2021
    Wydawca:
    Polskie Towarzystwo Promocji Wiedzy
    Tematy:
    search engine optimization
    Google
    page ranking
    information retrieve
    optymalizacja wyszukiwarek
    ranking stron
    pobieranie informacji
    Opis:
    The Search Engine has a critical role in presenting the correct pages to the user because of the availability of a huge number of websites, Search Engines such as Google use the Page Ranking Algorithm to rate web pages according to the nature of their content and their existence on the world wide web. SEO can be characterized as methodology used to elevate site keeping in mind the end goal to have a high rank i.e., top outcome. In this paper the authors present the most search engine optimization like (Google, Bing, MSN, Yahoo, etc.), and compare by the performance of the search engine optimization. The authors also present the benefits, limitation, challenges, and the search engine optimization application in business.
    Źródło:
    Applied Computer Science; 2021, 17, 1; 70-80
    1895-3735
    Pojawia się w:
    Applied Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Falcon optimization algorithm for bayesian network structure learning
    Autorzy:
    Kareem, Shahab Wahhab
    Okur, Mehmet Cudi
    Powiązania:
    https://bibliotekanauki.pl/articles/2097968.pdf
    Data publikacji:
    2021
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    Bayesian network
    global search
    falcon optimization algorithm
    structure learning
    search and score
    Opis:
    In machine-learning, some of the helpful scientific models during the production of a structure of knowledge are Bayesian networks. They can draw the relationships of probabilistic dependency among many variables. The score and search method is a tool that is used as a strategy for learning the structure of a Bayesian network. The authors apply the falcon optimization algorithm (FOA) to the learning structure of a Bayesian network. This paper has employed reversing, deleting, moving, and inserting to obtain the FOA for approaching the optimal solution of a structure. Essentially, the falcon prey search strategy is used in the FOA algorithm. The result of the proposed technique is associated with pigeon-inspired optimization, greedy search, and simulated annealing that apply the BDeu score function. The authors have also examined the performances of the confusion matrix of these techniques by utilizing several benchmark data sets. As shown by the experimental evaluations, the proposed method has a more reliable performance than other algorithms (including the production of excellent scores and accuracy values).
    Źródło:
    Computer Science; 2021, 22 (4); 553--569
    1508-2806
    2300-7036
    Pojawia się w:
    Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Enhancing approach using hybrid pailler and RSA for information security in bigdata
    Autorzy:
    Abdalwahid, Shadan Mohammed Jihad
    Yousif, Raghad Zuhair
    Kareem, Shahab Wahhab
    Powiązania:
    https://bibliotekanauki.pl/articles/117665.pdf
    Data publikacji:
    2019
    Wydawca:
    Polskie Towarzystwo Promocji Wiedzy
    Tematy:
    BigData
    Hadoop
    RSA
    Paillier
    Cryptography
    kryptografia
    Opis:
    The amount of data processed and stored in the cloud is growing dramatically. The traditional storage devices at both hardware and software levels cannot meet the requirement of the cloud. This fact motivates the need for a platform which can handle this problem. Hadoop is a deployed platform proposed to overcome this big data problem which often uses MapReduce architecture to process vast amounts of data of the cloud system. Hadoop has no strategy to assure the safety and confidentiality of the files saved inside the Hadoop distributed File system (HDFS). In the cloud, the protection of sensitive data is a critical issue in which data encryption schemes plays avital rule. This research proposes a hybrid system between two well-known asymmetric key cryptosystems (RSA, and Paillier) to encrypt the files stored in HDFS. Thus before saving data in HDFS, the proposed cryptosystem is utilized for encrypting the data. Each user of the cloud might upload files in two ways, non-safe or secure. The hybrid system shows higher computational complexity and less latency in comparison to the RSA cryptosystem alone.
    Źródło:
    Applied Computer Science; 2019, 15, 4; 63-74
    1895-3735
    Pojawia się w:
    Applied Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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