Smart rendering approach base on document structure analysis and user behavior tracking
Original Publication Date: 2008-Aug-14
Included in the Prior Art Database: 2008-Aug-14
AbstractThis method saves the time of users when they browse on Web. Today a lot of Web pages are longer than one screen height. When user browses Web pages , typically user needs scroll up and down to find the appropriate window frame which contains the content he is interested in, and then do some action.
Smart rendering approach base on document structureanalysis and user behavior tracking
This method saves the time of users when they browse on Web. Today a lot of Web pages are longer than one screen height. When user browses Web pages , typically user needs scroll up and down to find the appropriate window frame which contains the content he is interested in, and then do some action.
when a user wants to buy a book on Amazon, typically either through search or browse, he finds a book. But when he opens the detailed
information page of the book, it's quite long. In includes basically more than 10 items:"Better Together, Customers Who Bought This Item Also Bought, Editorial Reviews, Product Details, Look Inside This Book,… Customer Reviews…". But this user trusts mostly on the "Customer Reviews" information. Unfortunately, He has to scroll the page down aboutfour times of the window height in order to see the "Customer Reviews". See below picture.
Figure 1. screen shot for Amazon's detailed information page of a book
This is a quite boring and tedious work. If the user has to check several books, he has to do the scrolling every time.
Currently , no known solutions to this problem.
2. Summary of Invention:
The core idea of this invention is to providing more smart rendering for user in a certain context. Normally, user browses with a certain context in a continuous time period like above sample view "Customer Reviews" of a book. But the context may switch from one to another.
Today a lot of pages are generated by back-end database, that gives a foundation for this method. Because page A and B are the same ones generated by a backend database, thus in a short continuous time slot, the action user takes on page A are likely to take on page B.
Also in a single page, user's action is focused on one area. In the above Amazon sample, user's actionis to view "Customer Reviews". The likelihood of an action in page A is more and more likely to happen in another page Z, if the action happens again and again from page B to page Y in current time slot of user's work context.
Through the recognitio...