CAREER: Relaxed Content and Structure Queries over Heterogeneous Data

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。传统的“纯结构”数据库世界和“纯文本”信息检索世界之间的分离正在消失。数据库现在通常包括文本部分，而文件则增加了结构信息。这个项目的目标是设计新的技术和开发工具，以有效地查询和检索相关的信息在异构数据环境中的灵活性的条件上的内容，数据的结构，和查询的响应是可取的。该项目的第一个主要贡献是设计了质量评分机制，以综合的方式统一内容和结构评分。评分技术考虑到查询和答案之间的相似性来分配分数。该项目的第二个主要贡献是开发异构数据索引结构和查询处理算法，以有效地识别准确和近似的查询答案，并按照与查询相关的顺序提供答案。从这个项目产生的工作将通过深入研究的评分策略的答案质量和性能实验的查询处理技术的影响进行评估。预计该项目的成果将使用户能够在各种不同的数据环境中确定最适合其需要的数据，而不需要事先了解基本数据模式或内容。该项目通过课程开发、学生咨询和向计算机科学领域的妇女推广，将研究和教育结合起来。该项目的成果，包括出版物、数据集和软件，将在项目网站（http：//www.cs.rutgers.edu/RelaxedQ/）上公布。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).The traditional separation between the "structure-only" Database world and the "text-only" Information Retrieval world is fading. Databases now routinely include text components while documents are being augmented with structural information. The goal of this project is to design novel techniques and develop tools to efficiently query and retrieve relevant information in a heterogeneous data environment where flexibility in conditions on both the content, the structure of the data, and the response to a query is desirable. The first main contribution of the project is the design of quality scoring mechanisms that unify content and structure score in an integrated fashion. The scoring techniques take into account the similarity between the query and the answer to assign scores. The second main contribution of the project is the development of heterogeneous data index structures and query processing algorithms to efficiently identify exact and approximate query answers and provide the answers in the order of relevance to a query. The work resulting from this project will be evaluated through an in-depth study of the impact of the scoring strategies on answer quality and performance experiments on the query processing techniques. The results of this project are expected to enable users to identify the data that best fits their needs, in a variety of heterogeneous data environments, without requiring some preexisting knowledge of the underlying data schema or content. This project integrates research and education through curriculum development, student advising, and outreach to women in Computer Science. Results of this project, including publications, data sets and software will be made available on the project website (http://www.cs.rutgers.edu/~amelie/RelaxedQ/).