For a web page not suitable for splitting, auto-positioning or scrolling-by-block is used to assist the browsing as an alterative. A page adaptation technique is also developed to analyze the structure of an existing web page and split it into small and logically related units that fit into the screen of a mobile device. A web page is organized into a two level hierarchy with a thumbnail representation at the top level for providing a global view and index to a set of sub-pages at the bottom level for detail information. In this paper, we propose a new browsing convention to facilitate navigation and reading on a small-form-factor device. However, because most available web pages are designed for desktop PC in mind, it is inconvenient to browse these large web pages on a mobile device with a small screen. Mobile devices have already been widely used to access the Web. Experimental results show that our noise elimination technique is able to improve the mining results significantly. The proposed technique is evaluated with two data mining tasks, Web page clustering and classification. The SST is employed to detect and eliminate noises in any Web page of the site by mapping this page to the SST. We then introduce an information based measure to determine which parts of the SST represent noises and which parts represent the main contents of the site. By sampling the pages of the site, a Style Tree can be built for the site, which we call the Site Style Tree (SST). Based on this observation, we propose a tree structure, called Style Tree, to capture the common presentation styles and the actual contents of the pages in a given Web site. In this paper, we propose a noise elimination technique based on the following observation: In a given Web site, noisy blocks usually share some common contents and presentation styles, while the main content blocks of the pages are often diverse in their actual contents and/or presentation styles. Eliminating these noises is thus of great importance. We show that the information contained in these noisy blocks can seriously harm Web data mining. We call these blocks that are not the main content blocks of the page the noisy blocks. Apart from the main content blocks, it usually has such blocks as navigation panels, copyright and privacy notices, and advertisements (for business purposes and for easy user access). The text you end up with can be downloaded or copied to the clipboard, and you might find that you don't need anything more advanced than this.A commercial Web page typically contains many information blocks. I2OCR is a competent, free, online text extraction utility that gets you your text in a few seconds and through a straightforward step-by-step process. The application is available for Windows and macOS, and costs $50 after a free trial. Again, it's just a question of selecting the image with the text, and then you'll find it on your clipboard. The versatile Snagit is another option-the software covers screen capture, screen recordings, video editing, image annotations, and much more besides text extraction. It'll set you back a one-off fee of $8, but you can try it for free, and it comes with bonus extras such as a text-to-speech feature. TextSniper is a polished, intuitive tool for macOS that lets you quickly drag a selection box over the text you want to capture, which is then extracted and sent to the clipboard. Plenty of third-party apps will extract text from images for you as well. TextSniper works in seconds on any image on macOS.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |