QIC: Query in Context for Educational Collections

由于其可访问性和内容的爆炸性增长，NSDL存储库处于提供教师和其他知识寻求者所需的高质量材料的主要位置。然而，研究表明教师对在线资源不满意。当搜索合适的材料时，他们对耗时的手动检索和审查每个链接感到沮丧。这通常会导致满足于足够好的内容。为了保持和提高NSDL优质资源的利用率，开发一种更复杂的查询和检索方法是很重要的。教育馆藏上下文查询（QIC）是一项利用上下文敏感检索、语义查询分析和概念提取技术来创建教育馆藏便携式统一知识发现系统的研究项目。QIC最大限度地减少了提取过程中的人为干预，并减少了显示的上下文不准确结果的数量。它通过将信息过载的负担从用户转移到计算机上，彻底改变了个人搜索。QIC的功能扩展了NSDL的NCore搜索服务，而无需对数字集合的格式和组织进行重大更改，也无需对用户提供的大量额外数据进行更改。通过QIC，教师可以在最初检索的条目中找到相关信息，从而通过减少时间和精力来提高满意度。这种有效性提高了数字图书馆的利用率，鼓励知识寻求和思想探索。这有助于NSDL和合作伙伴馆藏的可持续性。QIC的长期目标是通过发现多种格式的信息并结合Web2.0工具来改进结果的显示和相关性，从而提供个性化的信息检索。

With its accessibility and explosive growth of content, the NSDL repositories are in a prime position to provide quality material teachers and other knowledge seekers need. Still, studies show teachers' dissatisfaction with online resources. They are frustrated with the time-consuming manual effort to retrieve and review each link when searching for appropriate material. This often leads to settling for good enough content. To sustain and increase the utilization of NSDL's quality resources, it is important a more sophisticated methodology for query and retrieval be developed.Query in Context for Educational Collections (QIC) is a research project utilizing context sensitive retrieval, semantic query analysis, and concept extraction techniques to create QIC's portable unified knowledge discovery system. QIC minimizes human intervention in the extraction process and reduces the number of contextually inaccurate results displayed. It revolutionizes individual search by shifting the burden of information overload from the user to the computer. QIC's functionality extends NSDL's NCore search services without significant changes to the format and organization of digital collections or extensive additional user provided data. With QIC, teachers find relevant information in the initially retrieved entries, thereby increasing satisfaction through reduced time and effort. This effectiveness improves digital library utilization, encourages knowledge seeking, and idea exploration. This contributes to the sustainability of NSDL and partner collections. QIC's long-term goal is to provide personalized information retrieval by discovering information in multiple formats and incorporating Web2.0 tools to improve the display and relevance of results.