Automatic identification and role detection of visual elements in web pages

Download

index.pdf

Date

2014

Author

Akpınar, Mehmet Elgin

Metadata

Show full item record

Item Usage Stats

203
views

105
downloads

Web pages typically include many visual elements to support interaction with the user. However, if visual elements do not comply with web accessibility guidelines, they become inaccessible in alternative presentations, such as audio. This study presents an automatic role detection approach to identify visual elements in web pages and their roles. The system architecture has three major components: automatic identification of visual elements in web pages; automatic generation of heuristic rules from the knowledge base; and application of these rules for automatic annotation of visual elements with their roles. Moreover, automatic role detection approach is deployed in a case study of web page transcoding based on eye tracking. This thesis first explains the system architecture in detail and then presents both technical and user evaluations of the proposed approaches. User evaluation shows that the automatic role detection approach has around 80% receptive accuracy, but the proposed knowledge base could be further improved for better results. User evaluation also shows that the transcoding application partially improves the information quality of web pages.

Subject Keywords

Web sites., Image processing., Ontology., Heuristic algorithms.

URI

http://etd.lib.metu.edu.tr/upload/12617704/index.pdf
https://hdl.handle.net/11511/23980

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Discovering Visual Elements of Web Pages and Their Roles: Users' Perception Akpinar, M. Elgin; Yesilada, Yeliz (2017-11-01) Web pages typically include many visual elements such as header and footer to support interaction with the user. However, if web pages do not comply with web accessibility guidelines, and these visual elements are not explicitly encoded in the underlying source code, they become inaccessible in alternative presentations, such as audio. This article presents an automatic role detection approach to identify visual elements in web pages and their roles. The system architecture has three major components: autom...
Improving the prediction of page access by using semantically enhanced clustering Şen, Erman; Toroslu, İsmail Hakkı; Karagöz, Pınar; Department of Computer Engineering (2014) There are many parameters that may affect the navigation behaviour of web users. Prediction of the potential next page that may be visited by the web user is important, since this information can be used for prefetching or personalization of the page for that user. One of the successful methods for the determination of the next web page is to construct behaviour models of the users by clustering. The success of clustering is highly correlated with similarity measure that is used for calculating the similari...
Automated test code generation and execution system for Web İşler, Süleyman Fatih; Betin Can, Aysu; Department of Information Systems (2015) With the development of Web 2.0, the trend in application development has moved from desktop applications towards to web applications. Although there are different ways of testing web applications such as record/replay systems and manual testing, the common practice of web testing is accomplished by manually implementing test script codes from test cases written in software test documents and then run them on test automation tools. Implementation of test script codes is time-consuming process and also requi...
PATTERNS IN EYETRACKING SCANPATHS AND THE AFFECTING FACTORS Eraslan, Sukru; Yesilada, Yeliz (2015-11-01) Web pages are typically decorated with different kinds of visual elements that help sighted people complete their tasks. Unfortunately, people accessing web pages in constrained environments, such as visually disabled and small screen device users, cannot benefit from them. In our previous work, we show that tracking the eye movements of sighted users provide good understanding of how people use these visual elements. We also show that reengineering web pages by using these visual elements can improve peopl...
Predicting Trending Elements on Web Pages Using Eye-Tracking Data Shekh Khalil , Naziha; Yeşilada, Yeliz; Eraslan, Şükrü; Computer Engineering (2022-8-31) Eye-tracking data can be used to understand how users interact with web pages and such understanding can be facilitated for different purposes, for example, it can be used to support better accessibility for disabled users or better usability for all users. However, understanding the sequential behavior of a group of users is challenging from eye-tracking data because individual eye movement sequences, i.e. scanpaths, tend to be complicated and different from each other. Previous work proposes an algorithm ...

Citation Formats

M. E. Akpınar, “Automatic identification and role detection of visual elements in web pages,” M.S. - Master of Science, Middle East Technical University, 2014.