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Sequoia—An Approach to Declarative Information Retrieval

机译:红杉—一种声明式信息检索方法

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摘要

In this work, we propose an approach that allows to query heterogeneous data sources on the Web in a declarative fashion. Such an approach gives means for a generic way to formulate various information needs, much more powerful than simple keyword queries. Particularly appealing is the ability to combine (join) information from different sources and the ability to compute simple statistics that can be used to select promising information pieces. What might sound like a hopeless effort due to the inherent complexity expressible by SQL-style queries is at second glance not complicated to understand and to use. Already very simple combinations (i.e., joins) of different data sources (i.e., tables) offer a surprisingly large set of interesting use cases. In particular, using sliding window joins that limit the scope of interest to recent information, obtained, for instance, from the live stream of Twitter Tweets. This goes far beyond keyword queries enriched with operators like allintext: or allintitle: or site:, as can be used, for instance, in the Google search engine.
机译:在这项工作中,我们提出了一种允许以声明方式查询Web上异构数据源的方法。这种方法提供了一种表达各种信息需求的通用方法,比简单的关键字查询功能强大得多。尤其吸引人的是能够合并(合并)来自不同来源的信息的能力以及计算可用于选择有前途的信息片段的简单统计信息的能力。乍一看,由于SQL样式查询可表达的固有复杂性,这听起来似乎是没有希望的工作,但乍一看,它并不易于理解和使用。不同数据源(即表)的非常简单的组合(即联接)提供了令人惊讶的大量有趣的用例。特别是,使用滑动窗口联接将关注范围限制在例如从Twitter Tweets的实时流中获取的最新信息。这远远超出了关键字查询,查询关键字中充斥了诸如allintext:或allintitle:或site:之类的运算符,例如可以在Google搜索引擎中使用的查询。

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