Improved Web Page Identification Method Using Neural Networks
نویسندگان
چکیده
In this paper, an improved web page classification method (IWPCM) using neural networks to identify the illicit contents of web pages is proposed. The proposed IWPCM approach is based on the improvement of feature selection of the web pages using class based feature vectors (CPBF). The CPBF feature selection approach has been calculated by considering the important term's weight for illicit web documents and reduce the dependency of the less important term's weight for normal web documents. The IWPCM approach has been examined using the modified term-weighting scheme by comparing it with several traditional term-weighting schemes for non-illicit and illicit web contents available from the web. The precision, recall, and F1 measures have been used to evaluate the effectiveness of the proposed IWPCM approach. The experimental results have shown that the proposed improved term-weighting scheme has been able to identify the non-illicit and illicit web contents available from the experimental datasets.
منابع مشابه
Aircraft Visual Identification by Neural Networks
In the present paper, an efficient method for three dimensional aircraft pattern recognition is introduced. In this method, a set of simple area based features extracted from silhouette of aerial vehicles are used to recognize an aircraft type from its optical or infrared images taken by a CCD camera or a FLIR sensor. These images can be taken from any direction and distance relative to the fly...
متن کاملComparison Study on Neural Networks in Damage Detection of Steel Truss Bridge
This paper presents the application of three main Artificial Neural Networks (ANNs) in damage detection of steel bridges. This method has the ability to indicate damage in structural elements due to a localized change of stiffness called damage zone. The changes in structural response is used to identify the states of structural damage. To circumvent the difficulty arising from the non-linear n...
متن کاملWeb Page Evaluation based on Implicit User Reactions and Neural Networks
This paper proposes a method for evaluating web pages by considering implicit user reaction on web pages. Usually users spend more time and make more reactions, such as clicking, dragging and scrolling, while reading interesting pages. Based on this observation, a web page evaluation method by observing implicit user reaction is proposed. The system is designed with Ajax for observing user reac...
متن کاملWeb page feature selection and classification using neural networks
Automatic categorization is the only viable method to deal with the scaling problem of the World Wide Web (WWW). In this paper, we propose a news web page classification method (WPCM). The WPCM uses a neural network with inputs obtained by both the principal components and class profile-based features. Each news web page is represented by the term-weighting scheme. As the number of unique words...
متن کاملSOM Improved Neural Network Approach for Next Page Prediction
The increasing usage of web results the heavy communication and slow returns from web. Because of this, there is the requirement of some approaches to optimize the web resources usage. One of such approach is caching that can be used within an organization to optimize the access of frequently used web pages. Caching is about to predict the requirement of next web access of a user and load it in...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- International Journal of Computational Intelligence and Applications
دوره 10 شماره
صفحات -
تاریخ انتشار 2011