مشخصات مقاله | |
ترجمه عنوان مقاله | طبقه بندی صفحه وب با استفاده از شبکه عصبی برگشتی (RNN) |
عنوان انگلیسی مقاله | Web Page Classification Using RNN |
انتشار | مقاله سال 2019 |
تعداد صفحات مقاله انگلیسی | 11 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس نمیباشد |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
1.257 در سال 2018 |
شاخص H_index | 47 در سال 2019 |
شاخص SJR | 0.281 در سال 2018 |
شناسه ISSN | 1877-0509 |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | ندارد |
رفرنس | دارد |
رشته های مرتبط | مهندسی کامپیوتر، مهندسی فناوری اطلاعات |
گرایش های مرتبط | هوش مصنوعی، اینترنت و شبکه های گسترده |
نوع ارائه مقاله |
ژورنال و کنفرانس |
مجله / کنفرانس | علوم کامپیوتر پروسیدیا-Procedia Computer Science |
دانشگاه | Computer Engineering Department, Yildiz Technical University, Istanbul, Turkey |
کلمات کلیدی | طبقه بندی صفحه وب، طبقه بندی، دسته بندی، یادگیری عمیق، شبکه عصبی برگشتی (RNN)، یادگیری انتقالی |
کلمات کلیدی انگلیسی | web page classification; classification; categorization; deep learning; RNN; transfer learning |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.procs.2019.06.011 |
کد محصول | E12277 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract
1. Introduction 2. Problem Definition 3. Web Page Classification 4. Experimental Results 5. Conclusion and Future Work 6. Acknowledgements 7. References |
بخشی از متن مقاله: |
Abstract
Web page classification is an information retrieval application that provides useful information that can be a basis for many different application domains. In this study, a deep learning-based system has been developed for the classification of web pages. The meta tag information contained in the web page is used to classify a web page. The meta tags used are title, description and keywords. RNN based deep learning architecture was used during the tests. Transfer learning is the name given to the approach to building a machine learning model with the use of pre-trained parameters to solve a problem. The effect of using transfer learning on the system has also been examined. According to the results obtained, success rate of web page classification system is approximately 85%. It is not observed that transfer learning has significant contribution to the success rates. However, the use of transfer learning has reduced the consumed system resources. Introduction Web page classification is an information retrieval application that provides useful information that can be a basis for many different application domains. Categorizing web pages provides useful information for efficient internet use, spam filtering and many other application areas. Finding relevant results quickly from millions of web sites is a serious problem that must be solved for search engines. For this reason, some search engines needed to make topic-based classification on web pages so that results returned to users could be returned better. In addition to this, web pages need to be categorized so that internet usage policies can be determined for institutions or individual uses. Web page classification can also be used by cyber security applications by blocking web pages with malicious content before they are displayed by the user. The automatic classification of web pages requires that very large amounts of data be processed. Manuel web page classification is a costly process. For this reason, manually classified web pages constitute a very small portion of the current web pages. The Web Site is the name given to the structure of a group of web pages linked to each other in various ways. A large number of web pages can be found under a website. Web pages are linked to each other. |