Intelligent Ink Annotation Framework that uses User's Intention in Electronic Document Annotation
Hiroki Asai, Hayato Yamana · 2014
Annotating documents is one of the indispensable interaction between human and documents. The annotation system of electronic documents enables to implement effective functions, such as information retrieval and annotation-based navigation, by using the annotation information; however, traditional systems require users to perform gestures in addition to common gestures for paper-based documents. This can reduce "learnability" of the system. We propose an intelligent ink annotation framework that helps the system to increase the learnability of annotation systems by detecting recognizable intentions from natural annotation behavior on paper-based documents. Our framework recognizes "Targeting Content" and "Commenting," which are related to extraction of annotation information. We have developed a prototype annotation system using our proposed framework and conducted a user study to identify future direction.