SBIR Phase II: Knowledge Discovery based on Personal Web Content Annotation

This Small Business Innovation Research (SBIR) Phase II project aims to develop a Recommendation System that offers users links to relevant pages as they browse the Web. As users interact with a Web page annotation platform, they use tools, such as highlighters and sticky notes, to annotate pages. The System is able to leverage these annotations to accurately model the user's information need, and to deliver high-quality recommendations. This Phase II project builds upon a prototype developed in Phase I, applying techniques from the information retrieval and natural language processing research communities to improve recommendation quality. This project encompasses primary research in document modeling, index representations and retrieval models. Further, the project proposes interesting synergies by drawing in methods from the text categorization, topic detection and tracking and collaborative filtering communities. The Broader Impact of this work lies in its potential to positively impact the task of doing research on the web. The company's nascent Web annotation Platform promises to save users time, reducing cost and frustration by providing content management and organizational structures that allow them to preserve state between web research sessions. The next step is to deploy the Recommendation System to bring users the next page they need before they even realize they need it. Individual users and businesses alike will derive value from the time savings provided by the company's Platform and its Recommendation System.