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

该研究项目的目标是针对 XML 格式的半结构化数据提供高质量的关键字搜索结果。为了解决处理关键词搜索中固有歧义性的挑战，开发了基本技术和有效的搜索引擎，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。该项目包括以下关键领域的新颖研究：（1）查询结果生成：识别XML数据中的相关节点并组成原子且完整的查询结果，每个查询结果代表推断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、片段生成和结果聚类技术，以帮助用户快速找到最相关的结果； (3) 高级查询和数据模型：支持表达搜索选项并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，还启动了一个公理评估框架，用于对 XML 关键字搜索策略进行形式推理。 该项目的成功将推动 XML 数据关键字搜索的最先进水平，增强该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、研讨会和外展计划与教育相结合。该项目产生的出版物、软件和课程材料将通过项目网站（http://www.public.asu.edu/~ychen127/xseek/）传播。

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://www.public.asu.edu/~ychen127/xseek/).