Web Browser Responsive to the Webdevelopment - Codeshoppy

 Web Browser Responsive to the Webdevelopment - Codeshoppy

we present the design of a web browser that is responsive to the user's interest level. The user's interest level is measured via a wearable Neurosky EEG sensor that gives a value of the user's attention level in real time. The current scroll position is used to identify which part of the webpage the user is reading currently. Combining the scroll position and the user's real time attention level, we identify which parts of the webpage, or which website in a list of currently open websites, the user is most interested in. We then make the web browser responsive to the attention level by adding the current webpage to the favorites if the attention level exceeds a threshold, removing a current webpage from the favorites if the attention level goes below a second threshold, generate on-the-fly an automatic index of the portions of the webpage that the user is more interested in from among the currently open tabs and so on. Having a responsive web browser that responds to the user's level of interest or disinterest can increase the user engagement or satisfaction while browsing. It can also be used to display targeted ads within the interesting portions of the webpage or design better web pages by giving the user interest feedback to the web developer. We describe the methodology and web browser architecture, some tests of the approach on different websites and user interfaces for making the web browser more responsive. Read More

Traditionally, web design depends on manual investigation by human. Each web design depends on their experience and individual style. We cannot focus on unity style easily. Besides, this clue, very few researches have been proposed to investigate good e-commerce web site design and make comparison with the other automatically. We are encountering with limitation of web site design improvement if we have to rely on the human judgment. We consider page segmentation  which can analyze the web site design, but most research has been studied on product extraction View More


 

we propose a method for analyzing page layout for assessing e-commerce web-site design. In order to discover the influencing factors, we need to divide the web page into individual blocks. Firstly, we divide each page into five blocks: top, bottom, left, right and center respectively. Secondly, we identify each e-commerce block to locate features such as navigation, product index and customer service. Finally, we consider e-commerce format and navigation menu style such as highlight, pop-up, text modification, row, and column appearance. In addition, we also consider the image alignment layout and text density. Then, we extract features to present the blocks and manually label their functions. After this pre-processing step, we need to label our data set according to block feature so that it can be used as the training set for classification algorithm. The accuracy result from the model will be used for our evaluation. We can select the appropriate model for implementing our system in the future. Click Here  

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