ITR: Querying Web Resources Using Metadata in a Database

本计画研究网路资讯资源之网路查询技术。术语信息资源指的是大型网络可访问资源，如ACM数字图书馆。我们提出了一种基于语义的访问Web信息资源的方法：从Web资源中提取关于主题和关系的元数据，用“重要性分数”扩展元数据，并从数据库中查询它。该查询语言被扩展为构造（a）将重要性分数传播到查询输出以对查询输出进行排名，以及（B）定义“停止条件”以减少查询评估时间。对于某些查询请求，数据库中的元数据可能不足以回答查询。我们的研究方向是在SQL查询的代数运算符级别上，通过将数据库查询与Web信息资源中的“聚焦爬行”相结合来定位更多信息的查询答案。这些查询允许时间限制，并放宽了封闭世界的假设，使得有必要重新定义定义明确的查询的概念。我们的基本方法，不需要直接的数据库查询引擎的变化将进行评估。将开发并提供独立的网络应用程序。

This project investigates web querying techniques for accessing web information resources. The term information resource refers to large web-accessible resources such as the ACM Digital Library. We propose a semantics-based way of accessing a web information resource: extract metadata about topics and relationships from the web resource, extend the metadata with "importance scores", and query it from a database. The query language is extended with constructs (a) to propagate importance scores to the query output to rank query output, and (b) to define "stopping conditions" to reduce query evaluation times.For some query requests, the metadata in the database may not be sufficient to answer queries. Our research direction is to locate more informative query answers by mixing database querying with "focused crawling" in the web information resource, at the algebraic operator level of SQL queries. These queries allow time constraints, and relax the closed world assumption, making it necessary to redefine the notion of well-defined queries.Data extraction techniques will be employed to extract metadata. Variations of our basic approach that do not require direct database query engine changes will be evaluated. Standalone web applications will be developed, and made available.