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

SBIR第二阶段：基于个人Web内容标注的知识发现

• 批准号: 0958266
• 负责人: Victor Karkar
• 金额: $ 50万
• 依托单位: skribel, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-03-01 至 2012-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0958266&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Knowledge; Discovery

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.

这个小企业创新研究（SBIR）第二阶段项目旨在开发一个推荐系统，在用户浏览网页时为他们提供相关页面的链接。当用户与Web页面注释平台交互时，他们使用诸如荧光笔和便利贴之类的工具来注释页面。系统能够利用这些注释准确地模拟用户的信息需求，并提供高质量的推荐。第二阶段的项目以第一阶段开发的原型为基础，应用信息检索和自然语言处理研究社区的技术来提高推荐质量。该项目包括文档建模、索引表示和检索模型方面的初步研究。此外，该项目通过引入文本分类、主题检测和跟踪以及协同过滤社区的方法，提出了有趣的协同效应。这项工作的更广泛的影响在于它有可能积极地影响在网络上做研究的任务。该公司新生的Web注释平台承诺，通过提供内容管理和组织结构，使用户能够在Web研究会议之间保持状态，从而节省用户的时间，减少成本和挫败感。下一步是部署推荐系统，让用户在意识到自己需要之前就找到他们需要的下一个页面。个人用户和企业都将从公司的平台和推荐系统节省的时间中获得价值。