Web Content Extraction

Weninger, Tim; Palacios, Rodrigo; Crescenzi, Valter; Gottron, Thomas; Merialdo, Paolo

doi:10.1145/2897350.2897353

Cited by 15 publications

(3 citation statements)

References 25 publications

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“…Thus, it is necessary to let the Web browser extract the interaction relevant elements of a Web page and observe changes in their properties. However, the introspection of elements in combination with the dynamics of Web pages are not yet reflected in Web page data extraction research, which is mostly focused on pure content extraction [16,83]. Recent work describes methods that allow for observation of preselected, dynamic elements [12,53].…”

Section: Methods For Interface Introspectionmentioning

confidence: 99%

Improving User Experience of Eye Tracking-Based Interaction

Menges

Kumar

Staab

2019

ACM Trans. Comput.-Hum. Interact.

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Eye tracking systems have greatly improved in recent years, being a viable and affordable option as digital communication channel, especially for people lacking fine motor skills. Using eye tracking as an input method is challenging due to accuracy and ambiguity issues, and therefore research in eye gaze interaction is mainly focused on better pointing and typing methods. However, these methods eventually need to be assimilated to enable users to control application interfaces. A common approach to employ eye tracking for controlling application interfaces is to emulate mouse and keyboard functionality. We argue that the emulation approach incurs unnecessary interaction and visual overhead for users, aggravating the entire experience of gaze-based computer access. We discuss how the knowledge about the interface semantics can help reducing the interaction and visual overhead to improve the user experience. Thus, we propose the efficient introspection of interfaces to retrieve the interface semantics and adapt the interaction with eye gaze. We have developed a Web browser, GazeTheWeb, that introspects Web page interfaces and adapts both the browser interface and the interaction elements on Web pages for gaze input. In a summative lab study with 20 participants, GazeTheWeb allowed the participants to accomplish information search and browsing tasks significantly faster than an emulation approach. Additional feasibility tests of GazeTheWeb in lab and home environment showcase its effectiveness in accomplishing daily Web browsing activities and adapting large variety of modern Web pages to suffice the interaction for people with motor impairment.

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Section: Methods For Interface Introspectionmentioning

confidence: 99%

Improving User Experience of Eye Tracking-Based Interaction

Menges

Kumar

Staab

2019

ACM Trans. Comput.-Hum. Interact.

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“…Most crawling techniques are based on the analysis of the HTML code of the Web pages, disregarding many aspects that have an impact on the resulting page, such as client side scripts, asynchronous functions, or CSS styles, some of which may even alter the DOM tree and contents of the HTML page [95]. Furthermore, crawlers are usually neglecting elements that may contribute to a more efficient and effective performance, such as HTML5 semantic tags or microformats, amongst others.…”

Section: Crawling Paths Learningmentioning

confidence: 99%

“…Note that this also results in better scalability, which is another main concern [70]. -Automatically update the crawled pages to improve their freshness [19,31,71,73,95,104].…”

Section: Performance Measuresmentioning

confidence: 99%

Deep Web crawling: a survey

2018

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Deep Web crawling refers to the problem of traversing the collection of pages in a deep Web site, which are dynamically generated in response to a particular query that is submitted using a search form. To achieve this, crawlers need to be endowed with some features that go beyond merely following links, such as the ability to automatically discover search forms that are entry points to the deep Web, fill in such forms, and follow certain paths to reach the deep Web pages with relevant information. Current surveys that analyse the state of the art in deep Web crawling do not provide a framework that allows comparing the most up-to-date proposals regarding all the different aspects involved in the deep Web crawling process. In this article, we propose a framework that analyses the main features of existing deep Web crawling-related techniques, including the most recent proposals, and provides an overall picture regarding deep Web crawling, including novel features that to the present day had not been analysed by previous surveys. Our main conclusion is that crawler evaluation is an immature research area due to the lack of a standard set of performance measures, or a benchmark or publicly available dataset to evaluate the crawlers. In addition, we conclude that the future work in this area should be focused on devising crawlers to deal with ever-evolving Web technologies and improving the crawling efficiency and scalability, in order to create effective crawlers that can operate in real-world contexts.

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Robust Web Data Extraction Based on Unsupervised Visual Validation

Potvin

Villemaire

2019

Intelligent Information and Database Systems

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Web Content Extraction

Cited by 15 publications

References 25 publications

Improving User Experience of Eye Tracking-Based Interaction

Improving User Experience of Eye Tracking-Based Interaction

Deep Web crawling: a survey

Robust Web Data Extraction Based on Unsupervised Visual Validation

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