Toward large scale data-aware search: Ranking, indexing, resolution and beyond

Tao Cheng, K. Chang
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Abstract

As the Web has evolved into a data-rich repository, with the standard “page view,” current search engines are becoming increasingly inadequate. To realize data-aware search, toward searching for data entities on the Web, we have been developing the various aspects of an entity search system, including: entity ranking, entity indexing and parallelization, entity resolution, as well as generalization and customization. Preliminary results show the promise of our proposals, achieving high accuracy, efficiency and scalability. We will also summarize our contributions and point out interesting future directions along the line of enabling data-aware search on the Web.
面向大规模数据感知搜索:排名、索引、解析等
随着网络发展成为一个数据丰富的存储库,加上标准的“页面浏览”,当前的搜索引擎正变得越来越不合适。为了实现数据感知搜索,针对Web上的数据实体搜索,我们一直在开发实体搜索系统的各个方面,包括:实体排序、实体索引和并行化、实体解析以及泛化和定制。初步结果表明,该方法具有较高的精度、效率和可扩展性。我们还将总结我们的贡献,并指出在Web上实现数据感知搜索的有趣的未来方向。
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