SBIR Phase I: Embedding Trend Discovery Within Search Engines

SBIR 第一阶段：在搜索引擎中嵌入趋势发现

• 批准号: 0945040
• 负责人: Raul Valdes-Perez
• 金额: $ 14.5万
• 依托单位: Vivisimo, 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: 2010-01-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0945040&HistoricalAwards=false
• 关键词: SBIR; Phase; Embedding; Trend; Discovery

This Small Business Innovation Research (SBIR) Phase I research project aims to make trend discovery on text documents a mainstream activity within the familiar workflow of search engine users, by using a linguistic approach that leverages many years of prior commercial research and technology development. The objective of this research is to develop the right representations and algorithms, implement a prototype, experiment with the appropriate user interfaces to support both initial discovery and the end-user's assessment of the discovered trends, and evaluate the system's ability to enable insightful trends that are not available with normal use of search engines. Executives, market analysts, science and technology monitors, and government intelligence analysts all are concerned with finding trends. There are established commercial business-intelligence methods for finding and understanding trends in structured data. However, research accomplishments from trend detection in text data have not entered mainstream use because of complicated user experiences and an inability to discern what are truly emerging topics, rather than merely recurring salient topics or linguistic variations on old topics, e.g., "lawsuit" as an old topic and "litigation" as a new topic. If successfully embedded within the familiar search workflow, it is anticipated that trend discovery will be a boon to many knowledge-work professions, leading to early detection of changes that can impact science, technology, government, healthcare, and business performance.

这个小企业创新研究（SBIR）第一阶段的研究项目旨在通过使用语言学方法，利用多年的商业研究和技术开发，使文本文档的趋势发现成为搜索引擎用户熟悉的工作流程中的主流活动。本研究的目标是开发正确的表示和算法，实现原型，使用适当的用户界面进行实验，以支持初始发现和最终用户对所发现趋势的评估，并评估系统的能力，以实现正常使用搜索引擎无法获得的深刻趋势。高管、市场分析师、科技监督员和政府情报分析师都关心趋势的发现。已经建立了用于查找和理解结构化数据趋势的商业商业智能方法。然而，文本数据趋势检测的研究成果并没有进入主流使用，因为用户体验复杂，无法区分什么是真正的新兴话题，而不仅仅是重复出现的突出话题或旧话题的语言变体，例如“诉讼”是旧话题，“诉讼”是新话题。如果成功地嵌入到熟悉的搜索工作流程中，预计趋势发现将为许多知识工作专业人员带来福音，可以早期发现可能影响科学、技术、政府、医疗保健和业务绩效的变化。