CAREER: Analyzing and Exploiting Meta-information for Keyword Search on Semi-structured Data

职业：分析和利用元信息进行半结构化数据的关键字搜索

• 批准号: 1322406
• 负责人: Yi Chen
• 金额: $ 28.9万
• 依托单位: New Jersey Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-12-25 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1322406&HistoricalAwards=false
• 关键词: CAREER; Analyzing; Exploiting; Meta; information

The goal of this research project is to provide high-quality keyword search results on semi-structured data in XML format. To address the challenge of handling inherent ambiguity in keyword search, fundamental techniques and an effective search engine are developed that exploit the meta-information in the data in order to infer user search intention and to achieve high search quality. The project includes novel research on the following key areas: (1) Query Result Generation: identifying relevant nodes in XML data and composing atomic and intact query results, each of which represents an object of the inferred user search goal; (2) Query Result Presentation: developing techniques for result ranking, snippet generation, and result clustering, in order to help users quickly find the most relevant results; (3) Advanced Queries and Data Models: supporting expressive search options and handling XML data with rich constraints; and (4) Efficiency: developing techniques for performance optimization, including indexes, materialized views, and top-k query processing. Furthermore, an axiomatic evaluation framework is initiated for formally reasoning about XML keyword search strategies.The success of the project will advance the state-of-the-art of keyword search on XML data, enhance the research and education infrastructure in this area, and have broader impacts on both general public as well as scientific communities for information discovery. This research is intergrated with education through curriculum enhancement, student advising, workshops as well as outreach programs. Publications, software and course materials that are resulted from this project will be disseminated via the project website (http://web.njit.edu/~ychen/xseek.htm).

这个研究项目的目标是在XML格式的半结构化数据上提供高质量的关键字搜索结果。为了解决关键字搜索中固有歧义的处理挑战，开发了利用数据中的元信息来推断用户搜索意图并实现高搜索质量的基本技术和有效的搜索引擎。该项目包括以下关键领域的新研究：(1)查询结果生成：识别XML数据中的相关节点，组成原子和完整的查询结果，每个查询结果代表推断出的用户搜索目标的一个对象；(2)查询结果呈现：开发结果排序、代码片段生成和结果聚类技术，帮助用户快速找到最相关的结果；(3)高级查询和数据模型：支持富有表现力的搜索选项和处理具有丰富约束的XML数据；(4)效率：开发性能优化技术，包括索引、物化视图和top-k查询处理。此外，还提出了一个公理化评估框架，用于对XML关键字搜索策略进行形式化推理。该项目的成功将推动XML数据关键字搜索技术的发展，增强这一领域的研究和教育基础设施，并对公众和科学界的信息发现产生更广泛的影响。这项研究通过课程改进、学生咨询、研讨会以及外展计划与教育相结合。本项目产生的出版物、软件和课程材料将通过项目网站（http://web.njit.edu/~ychen/xseek.htm）发布。