基于视觉的隐马尔可夫树分类方法向有辅助需求的用户传递网页

2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI) Pub Date : 2016-10-01 DOI:10.1109/WI.2016.0124

M. Cormier, R. Mann, R. Cohen, Karyn Moffatt

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引用次数: 5

摘要

在本文中，我们概述了我们提出的基于内容和视觉属性对网页区域进行分类的算法。我们展示了隐马尔可夫树如何有效地进行分类，以及它如何最终为试图查看网页的用户提供改进的体验。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Classification via Hidden Markov Trees for a Vision-Based Approach to Conveying Webpages to Users with Assistive Needs

In this paper we present an overview of our proposed algorithms for classifying regions of web pages based on content and visual properties. We show how hidden Markov trees may be effective for the classification and how this may end up offering improved experiences to users who are trying to view webpages.

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来源期刊

2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI)

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