Beyond keyword search for ranked document retrieval

这个项目将开发新的方法来高效和有效的排名文本检索使用一类新的排名感知算法来自自索引。这些算法可以支持动态的复杂统计计算。大数据的高效算法设计是一个越来越重要的问题，因为能源成本持续飙升，现在可能超过谷歌等大数据消费者的硬件成本。在这个项目中，Web搜索中的两个重要问题进行了探讨：实时索引和长格式查询回答。使用自索引算法，该项目提出了一个路线图，超越简单的基于关键字的排名文档检索，从而使我们能够有效地满足用户在未来十年更苛刻的信息需求。

This project will develop novel approaches to efficient and effective ranked text retrieval using a new class of rank-aware algorithms derived from self-indexes. These algorithms can support complex statistical calculations on the fly. Efficient algorithm design for big data is an increasingly important problem as energy costs continue to soar and can now exceed hardware costs for big data consumers such as Google. In this project, two important problems in web search are explored: real-time indexing and long-form query answering. Using self-index algorithms, this project presents a road map to move beyond simple keyword-based ranked document retrieval, thus allowing us to efficiently meet more demanding information needs of users in the next decade.