Layout Based Information Extraction from HTML Documents

Burget, Radek

doi:10.1109/icdar.2007.4376990

Cited by 16 publications

(7 citation statements)

References 7 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%

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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%

“…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%

A Web Page Segmentation Approach Using Visual Semantics

Zeng

Flanagan

Hirokawa

et al. 2014

IEICE Trans. Inf. & Syst.

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“…Our segmentation algorithm (Burget, 2007), works in a bottom-up manner. Each block is represented by the coordinates of top-left and bottom-right point of a box.…”

Section: Phase I -Visual Block Classificationmentioning

confidence: 99%

Two-Phase Categorization of Web Documents

Bartík

Burget

2010

Proceedings of the International Conference on Knowledge Discovery and Information Retrieval

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The number of pages on the World Wide Web is permanently growing and there is a need to process pages efficiently and obtain some useful knowledge from them. Web page categorization is a very important issue in this area. The method proposed here takes both visual and textual information into consideration. It consists of two phases. In the first phase, web page areas obtained by segmentation are classified based on their visual properties, and in the second phase, pages are classified, based on information from the first phase and textual information. Several experiments with web pages taken from news web sites are presented in the final part of the paper.

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“…Processing of digital documents not having a strict layout is also faced by other works, such as Web pages (Feng, 2005;Burget, 2007;Guo, 2007) or email messages (Chao, 2005).…”

Section: Related Workmentioning

confidence: 99%

FOL Learning for Knowledge Discovery in Documents

et al. 2012

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This chapter proposes the application of machine learning techniques, based on first-order logic as a representation language, to the real-world application domain of document processing. First, the tasks and problems involved in document processing are presented, along with the prototypical system DOMINUS and its architecture, whose components are aimed at facing these issues. Then, a closer look is provided for the learning component of the system, and the two sub-systems that are in charge of performing supervised and unsupervised learning as a support to the system performance. Finally, some experiments are reported that assess the quality of the learning performance. This is intended to prove to researchers and practitioners of the field that first-order logic learning can be a viable solution to tackle the domain complexity, and to solve problems such as incremental evolution of the document repository.

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Layout Based Information Extraction from HTML Documents

Cited by 16 publications

References 7 publications

A Web Page Segmentation Approach Using Visual Semantics

A Web Page Segmentation Approach Using Visual Semantics

Two-Phase Categorization of Web Documents

FOL Learning for Knowledge Discovery in Documents

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