The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Visual Based Content Understanding towards Web Adaptation
AH '02 Proceedings of the Second International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
HTML Page Analysis Based on Visual Cues
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Using urls and table layout for web classification tasks
Proceedings of the 13th international conference on World Wide Web
Learning block importance models for web pages
Proceedings of the 13th international conference on World Wide Web
Using link analysis to improve layout on mobile devices
Proceedings of the 13th international conference on World Wide Web
Template-independent news extraction based on visual consistency
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Heuristic role detection of visual elements of web pages
ICWE'13 Proceedings of the 13th international conference on Web Engineering
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In this paper, we describe a method for understanding the function of web elements. It classifies web elements into five functional categories: Content (C), Related Links (R), Navigation and Support (N), Advertisement (A) and Form (F). We construct five graphs for a web page, and each graph is designed such that most of the probability mass of the stationary distribution is concentrated in nodes belong to its corresponding category. We perform random walks on these graphs until convergence and classify based on its rank value in different graphs. Our experiment shows that the new method performed very well comparing to basic machine learning methods.