Geraldine Wade

Summarizing personal web browsing sessions

We describe a system, implemented as a browser extension, that enables users to quickly and easily collect, view, and share personal Web content. Our system employs a novel interaction model, which allows a user to specify webpage extraction patterns by interactively selecting webpage elements and applying these patterns to automatically collect similar content. Further, we present a technique for creating visual summaries of the collected information by combining user labeling with predefined layout templates. These summaries are interactive in nature: depending on the behaviors encoded in their templates, they may respond to mouse events, in addition to providing a visual summary. Finally, the summaries can be saved or sent to others to continue the research at another place or time. Informal evaluation shows that our approach works well for popular websites, and that users can quickly learn this interaction model for collecting content from the Web.

Example-based hinting of true type fonts

Hinting in TrueType is a time-consuming manual process in which a typographer creates a sequence of instructions for better fitting the characters of a font to a grid of pixels. In this paper, we propose a new method for automatically hinting TrueType fonts by transferring hints of one font to another. Given a hinted source font and a target font without hints, our method matches the outlines of corresponding glyphs in each font, and then translates all of the individual hints for each glyph from the source to the target font. It also translates the control value table (CVT) entries, which are used to unify feature sizes across a font. The resulting hinted font already provides a great improvement over the unhinted version. More importantly, the translated hints, which preserve the sound, hand-designed hinting structure of the original font, provide a very good starting point for a professional typographer to complete and fine-tune, saving time and increasing productivity. We demonstrate our approach with examples of automatically hinted fonts at typical display sizes and screen resolutions. We also provide estimates of the time saved by a professional typographer in hinting new fonts using this semi-automatic approach.