عنوان المقالة: Filter Intolerable Posts from OSN User Walls
زهراء مظهر نبات العجرش | Zahraa Modher Nabat AL-Ajrash | 4565
نوع النشر
مجلة علمية
المؤلفون بالعربي
المؤلفون بالإنجليزي
Zahraa Modher Nabat, Hemant Mahajan
الملخص الانجليزي
As we know, these days everyone seems to be victimization On-line Social Networks (OSNs) to speak and share data. Therefore, one vital want in these days On-line Social Networks (OSNs) is to offer users the power to manage the messages denote on their own personal area to avoid that unwanted content is displayed. on-line informal communication (OSNs) has was a standout amongst the foremost current intelligent medium to impart, impart and disperse the human life knowledge. therefore, the increasing utilization of it incorporates providing of substance like free messages, pictures, sounds and options. that currently and once more isn't vulnerable to be imparted on users personal divider. For the nowadays OSNs have given a little backing to the present. For this reason, to be increased, we've got projected a framework that offers the OSN purchasers a right away management on such type of messages. This can be achieved through a versatile rule-based system that enables users to customize the filtering criteria to be applied to their walls, Machine Learning-based soft classifier mechanically labeling messages in support of content-based filtering. Online informal communication (OSNs) has was a standout amongst the foremost current intelligent medium to impart, impart and disperse the human life knowledge. Therefore, the increasing utilization of it incorporates providing of substance like free messages, pictures, sounds and options. that currently and once more isn't vulnerable to be imparted on users personal divider
تاريخ النشر
05/05/0016
الناشر
Zahraa Modher Nabat, Hemant Mahajan
رقم المجلد
رقم العدد
2007
ISSN/ISBN
2319-7064
رابط خارجي
https://pdfs.semanticscholar.org/7df5/597abd15dcc814d6d2178979b0e0a65ee4b7.pdf
الكلمات المفتاحية
International Journal of Engineering &Extended Technologies Research
رجوع