Comparative Study of Web Page Classification Approaches

Vinod, Pooja; Prajapati, Purvi

doi:10.5120/ijca2018916994

Cited by 9 publications

(5 citation statements)

References 6 publications

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“…As defined in [21], [22], [23], [24], web page classification involves the task of attributing one or more category labels to a web page. There are two primary methods for categorizing web pages: manual classification, where humans make the assignments, and automatic classification, which is performed by computer algorithms.…”

Section: Literature Review a Web Page Classificationmentioning

confidence: 99%

Use Word Cloud Image Of Web Page Text Content On Convolutional Neural Network (CNN) For Classification Of Web Pages

Hawa Apandi,

Sallim,

Mohamed

2024

IJCDS

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In the modern digital era, people easily access the internet to find information through website visits. Many individuals are attracted to online pages featuring games and video content. Prolonged exposure to such web pages can result in internet addiction, leading to negative consequences. To address this issue, it is crucial to impose restrictions on websites offering gaming and streaming content. To accomplish this, an essential tool is needed to classify web pages based on their content. In the categorization process, the text content of the web page is initially extracted. Since conventional matrix representations are not suitable for processing lengthy web page text, this study employs an innovative method involving the use of word cloud images to visually represent words extracted from the web page text after data pre-processing. Words that appear most frequently in the web page text are displayed in larger fonts and centered in the word cloud image, reflecting the subject matter of the web page. A Convolutional Neural Network (CNN) is then utilized to identify patterns in the central part of the word cloud image, facilitating the categorization of web pages based on their content. The proposed model for classifying web pages achieves an accuracy rate of 0.86, significantly improving the accuracy of web page categorization. By leveraging insights gained from web page classification, authorities can proactively monitor online user behavior, identifying individuals struggling with internet addiction and offering help if needed.

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Section: Literature Review a Web Page Classificationmentioning

confidence: 99%

Use Word Cloud Image Of Web Page Text Content On Convolutional Neural Network (CNN) For Classification Of Web Pages

Hawa Apandi,

Sallim,

Mohamed

2024

IJCDS

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“…For instance, subject classification would be determining whether a page is about arts, business, or sports. [5]. • Functional classification takes into consideration the function that the website page serves.…”

Section: Webpages Classification Typesmentioning

confidence: 99%

Webpage Classification Using Ensemble Machine Learning

Altaee

2023

IJICI

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These days, it is not easy to get the correct information after typing a keyword into a search engine because so many results are returned. Classification of Web pages is a technique that helps us locate the wanted information quickly and effectively. In addition, website categorization is crucial for businesses that provide marketing and analytical solutions because it enables them to create a well-balanced mix of search engine and directory listings. This will give marketers a better idea of where their local company listings appear online, allowing them to have more judgment about initiative and strategy. Therefore, the research aimed to construct a classification system based on a dataset of English web pages. This information has been acquired from the Kaggle website and consisted of 1408 distinct rows organized into 16 categories. The research has employed mixed strategies to determine which strategy for Web page categorization would yield the best results. The first strategy puts into practice a collection of machine-learning algorithms. It assesses how well they accomplish the given classification task. Ensemble stacking is the second strategy, and it is employed to enhance the classification of websites. Comparing the results of the two strategies reveals that Ensemble stacking, the second strategy, was the more influential architecture for classifying web pages this approach had 0.95 F1-score, 0.95 accuracy, 0.95 precision, and 0.95 recall achieved by this method. The first approach, which made use of machine learning techniques, on the other hand, received an F1-score of 0.93, 0.94 for precision, 0.93 for recall, and 0.93 for accuracy.

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“…The basic problem of classifying web pages can be subdivided into more specialized problems such as subject classification, functional classification, sentiment classification, and other sorts of classification. This study will concentrate on a specific aspect of web page classification known as subject classification, sometimes known as topic classification, in which web pages are classified based on their contents or the topic of the web page [3], [6], [7].…”

Section: A Web Page Classificationmentioning

confidence: 99%

Automatic Topic-Based Web Page Classification Using Deep Learning

Apandi,

Sallim,

Mohamed

et al. 2023

JOIV : Int. J. Inform. Visualization

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The internet is frequently surfed by people by using smartphones, laptops, or computers in order to search information online in the web. The increase of information in the web has made the web pages grow day by day. The automatic topic-based web page classification is used to manage the excessive amount of web pages by classifying them to different categories based on the web page content. Different machine learning algorithms have been employed as web page classifiers to categorise the web pages. However, there is lack of study that review classification of web pages using deep learning. In this study, the automatic topic-based classification of web pages utilising deep learning that has been proposed by many key researchers are reviewed. The relevant research papers are selected from reputable research databases. The review process looked at the dataset, features, algorithm, pre-processing used in classification of web pages, document representation technique and performance of the web page classification model. The document representation technique used to represent the web page features is an important aspect in the classification of web pages as it affects the performance of the web page classification model. The integral web page feature is the textual content. Based on the review, it was found that the image based web page classification showed higher performance compared to the text based web page classification. Due to lack of matrix representation that can effectively handle long web page text content, a new document representation technique which is word cloud image can be used to visualize the words that have been extracted from the text content web page.

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Comparative Study of Web Page Classification Approaches

Cited by 9 publications

References 6 publications

Use Word Cloud Image Of Web Page Text Content On Convolutional Neural Network (CNN) For Classification Of Web Pages

Use Word Cloud Image Of Web Page Text Content On Convolutional Neural Network (CNN) For Classification Of Web Pages

Webpage Classification Using Ensemble Machine Learning

Automatic Topic-Based Web Page Classification Using Deep Learning

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