Web Content Extraction based on Webpage Layout Analysis

Fu, Lei; Meng, Yao; Xia, Yingju; Yu, Hao

doi:10.1109/itcs.2010.16

Cited by 15 publications

(9 citation statements)

References 16 publications

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“…2(a) . Whereas C j is the label of the class such that * + with and , which indicates the membership of W j in the phish class or in the legitimate class based on its corresponding features [38,39] as portrayed in Fig. 2(b).…”

Section: A Test-bed and Featuresmentioning

confidence: 99%

The Effect of Feature Selection on Phish Website Detection

Zuhair¹,

Selmat²,

Salleh³

2015

ijacsa

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Abstract-Recently, limited anti-phishing campaigns have given phishers more possibilities to bypass through their advanced deceptions. Moreover, failure to devise appropriate classification techniques to effectively identify these deceptions has degraded the detection of phishing websites. Consequently, exploiting as new; few; predictive; and effective features as possible has emerged as a key challenge to keep the detection resilient. Thus, some prior works had been carried out to investigate and apply certain selected methods to develop their own classification techniques. However, no study had generally agreed on which feature selection method that could be employed as the best assistant to enhance the classification performance. Hence, this study empirically examined these methods and their effects on classification performance. Furthermore, it recommends some promoting criteria to assess their outcomes and offers contribution on the problem at hand. Hybrid features, low and high dimensional datasets, different feature selection methods, and classification models were examined in this study. As a result, the findings displayed notably improved detection precision with low latency, as well as noteworthy gains in robustness and prediction susceptibilities. Although selecting an ideal feature subset was a challenging task, the findings retrieved from this study had provided the most advantageous feature subset as possible for robust selection and effective classification in the phishing detection domain.

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Section: A Test-bed and Featuresmentioning

confidence: 99%

The Effect of Feature Selection on Phish Website Detection

Zuhair¹,

Selmat²,

Salleh³

2015

ijacsa

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show abstract

“…• degree of computerization for information extraction systems Fu et al (2010) described a method for guiding the content extraction process, using the webpage layout information. They proposed a four aspects on some specific websites, attribute to as web bases, that afford a complex HTML search form for the users to querying the back-end databases Wang (2003).…”

Section: Related Workmentioning

confidence: 99%

A Layout Based Detachment Approach for Extracting Content from Webpages

Chandran¹,

Vijendran²

2015

American Journal of Applied Sciences

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Enormous amount of useful information presented in Internet is usually formatted for the web users. But it is a really complex task to extract the relevant data from various web sources. Recently, various approaches for the extraction of data from the webpages were proposed. This study provides a simple but effective approach, named Layout Based Detachment Approach (LBDA). The proposed approach extracts the main content from the webpage by removing the irrelevant information like header-footer contents, navigation bars, advertisements and other noisy images. The proposed methodology uses the following techniques: Tag tree parsing to get the analysis structure, block acquiring page segmentation method to remove unwanted tags and data extraction to retrieve the necessary contents. The proposed approach eliminates noise and perform effective extraction of the main content blocks from the webpage and display of the essential content to the users. The performance of the proposed approach is evaluated using the performance metrics such as accuracy, precision, recall, execution time and memory usage. The implementation results obviously show that our proposed LBDA approach exhibits better performance than the existing heuristic approach.

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“…Some researchers proposed techniques [4] [5], which require multiple pages for the extraction process. Only some techniques [6] [7] are able to work on single page. In addition, some works proposed are only aimed to extract specific Web content such as shopping data, news.…”

Section: Related Workmentioning

confidence: 99%

Improving Webpage Content Extraction by extending a novel single page extraction approach: A case study with Thai websites

Thanadechteemapat

Fung

2012

2012 International Conference on Machine Learning and Cybernetics

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Abstract:Web Content Extraction technique is proposed in this paper. The technique is able to work with both single and multiple pages based on heuristic rules. An Extracted Content Matching (ECM) technique is proposed in the multiple page extraction to identify the noises among the extracted results. Some features in this technique are also introduced in order to reduce processing time such as use of XPath, file compression, and parallel processing. Assessment of the performance is based on precision, recall and F-measure by using the length of extracted content. Initial results by comparing results from the proposed approach to extraction by manual process are good.

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Web Content Extraction based on Webpage Layout Analysis

Cited by 15 publications

References 16 publications

The Effect of Feature Selection on Phish Website Detection

The Effect of Feature Selection on Phish Website Detection

A Layout Based Detachment Approach for Extracting Content from Webpages

Improving Webpage Content Extraction by extending a novel single page extraction approach: A case study with Thai websites

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