Web Page Element Classification Based on Visual Features

Burget, Radek; Rudolfova, Ivana

doi:10.1109/aciids.2009.71

Cited by 38 publications

(30 citation statements)

References 8 publications

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“…These methods also have some limitations, for example: these methods may falsely separate closely related contents and combine unrelated contents together. Some other heuristicsbased approaches rely on visual cues from browser renderings [2], [5]- [7], [10]. Most of them focus on the location, size or font cues of web pages.…”

Section: Copyright C 2014 the Institute Of Electronics Information Amentioning

confidence: 99%

“…Web page segmentation has a variety of benefits and potential web applications, such as browsing web pages on mobile devices [1]- [3], detecting duplicate web pages [4], information extraction [5]- [7].…”

Section: Introductionmentioning

confidence: 99%

“…The early techniques of web page segmentation are mainly based on machine learning algorithms [1], [4], [8], [9] and rule-based heuristics [2], [3], [5]- [7], [10]- [12], [15]. Because of the small scale training data set, machinelearning-based methods can only be applied in some certain fields of web pages.…”

Section: Introductionmentioning

confidence: 99%

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A Web Page Segmentation Approach Using Visual Semantics

Zeng

Flanagan

Hirokawa

et al. 2014

IEICE Trans. Inf. & Syst.

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SUMMARYWeb page segmentation has a variety of benefits and potential web applications. Early techniques of web page segmentation are mainly based on machine learning algorithms and rule-based heuristics, which cannot be used for large-scale page segmentation. In this paper, we propose a formulated page segmentation method using visual semantics. Instead of analyzing the visual cues of web pages, this method utilizes three measures to formulate the visual semantics: layout tree is used to recognize the visual similar blocks; seam degree is used to describe how neatly the blocks are arranged; content similarity is used to describe the content coherent degree between blocks. A comparison experiment was done using the VIPS algorithm as a baseline. Experiment results show that the proposed method can divide a Web page into appropriate semantic segments.

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Section: Copyright C 2014 the Institute Of Electronics Information Amentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Web Page Segmentation Approach Using Visual Semantics

Zeng

Flanagan

Hirokawa

et al. 2014

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

show abstract

“…The second approach assumes that the main content of a webpage is often located in the central part and (at least partially) visible without scrolling [5]. This approach has been less studied because rendering webpages for classification is a computational expensive operation [15].…”

Section: Related Workmentioning

confidence: 99%

Site-Level Web Template Extraction Based on DOM Analysis

Alarte

Insa

Silva

et al. 2016

Lecture Notes in Computer Science

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Abstract. One of the main development resources for website engineers are Web templates. Templates allow them to increase productivity by plugin content into already formatted and prepared pagelets. For the final user templates are also useful, because they provide uniformity and a common look and feel for all webpages. However, from the point of view of crawlers and indexers, templates are an important problem, because templates usually contain irrelevant information such as advertisements, menus, and banners. Processing and storing this information leads to a waste of resources (storage space, bandwidth, etc.). It has been measured that templates represent between 40% and 50% of data on the Web. Therefore, identifying templates is essential for indexing tasks. In this work we propose a novel method for automatic web template extraction that is based on similarity analysis between the DOM trees of a collection of webpages that are detected using an hyperlink analysis.Our implementation and experiments demonstrate the usefulness of the technique.

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“…Radek et al [8,9] propose a HTML content extraction method based on a page segmentation algorithm that splits rendered HTML pages into multiple basic areas that are visually separated from each other due to different background colors, frames or markup separators. Areas having similar visual characteristics are then clustered together into semantically correlated blocks which are assigned to different classes of interest on the basis of their font, spatial, text and color features.…”

Section: Related Workmentioning

confidence: 99%

Content Extraction from Marketing Flyers

Gallo

Zamberletti

Noce

2015

Computer Analysis of Images and Patterns

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Abstract. The rise of online shopping has hurt physical retailers, which struggle to persuade customers to buy products in physical stores rather than online. Marketing flyers are a great mean to increase the visibility of physical retailers, but the unstructured offers appearing in those documents cannot be easily compared with similar online deals, making it hard for a customer to understand whether it is more convenient to order a product online or to buy it from the physical shop. In this work we tackle this problem, introducing a content extraction algorithm that automatically extracts structured data from flyers. Unlike competing approaches that mainly focus on textual content or simply analyze font type, color and text positioning, we propose novel and more advanced visual features that capture the properties of graphic elements typically used in marketing materials to attract the attention of readers towards specific deals, obtaining excellent results and a high language and genre independence.

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Web Page Element Classification Based on Visual Features

Cited by 38 publications

References 8 publications

A Web Page Segmentation Approach Using Visual Semantics

A Web Page Segmentation Approach Using Visual Semantics

Site-Level Web Template Extraction Based on DOM Analysis

Content Extraction from Marketing Flyers

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