The quality of the web page classification process has a huge impact on information retrieval systems. In this paper, we proposed to combine results text and image data classifiers get an accurate representation pages. To analyse created complicated classifier system with miner, classifier, aggregator. been achieved by deep learning models. order represent common view onto pages, three aggregat...

Web characterization methods have been studied for many years. Most of these methods focus on textbased web contents. Some of them analyze the contents of a web page by analyzing its HTML code, hyper links, and/or DOM 1 structure. Seldom, a web page is characterized based on its visual appearance. A good reason for also considering the visual appearance of a web page is because humans initially...

Web pages are discriminated based on their topic and genre. Web page genres are capable to improve the modern search engines to focus on the user's information need. In this paper, web pages are represented using character n-grams. Character n-gram representation is language independent and allows automatic extraction of features from a web page. Character n-gram representation of a web pa...

The extraordinary growth in both the size and popularity of the World Wide Web has created a growing interest not only in identifying Web page genres, but also in using these genres to classify Web pages. The hypothesis of this research is that an n-gram representation of a Web page can be used effectively to automatically classify that Web page by genre. This research involves the development ...

ABSTARCT: As the information contained within the web is increasing day by day, organizing this information could be a necessary requirement.The data mining process is to extract information from a data set and transform it into an understandable structure for further use. Classification of web page content is essential to many tasks in web information retrieval such as maintaining web director...

The boom in the use of Web and its exponential growth are now well known. The amount of textual data available on the Web is estimated to be in the order of one terra byte, in addition to images, audio and video. This has imposed additional challenges to the Web directories which help the user to search the Web by classifying selected Web documents into subject. Manual classification of web pag...

Motivated by applying Text Categorization to classification of Web search results, this paper describes an extensive experimental study of the impact of bag-ofwords document representations on the performance of five major classifiers – Naïve Bayes, SVM, Voted Perceptron, kNN and C4.5. The texts, representing short Web-page descriptions sorted into a large hierarchy of topics, are taken from th...

In this paper, we propose a method for evaluation of relevance in Web pages. This work joins in the general framework of Information Retrieval (IR) and more precisely, with the aim of constructing an automatic summary in encyclopaedic style. This summary type allows a new approach of Web page classification. In this paper, we present our classification approach and we detail our method for Web ...