Design Patterns for Fusion-Based Object Retrieval
Design Patterns for Fusion-Based Object Retrieval
复制标题
基于融合的对象检索的设计模式
DOI：
10.1007/978-3-319-56608-5_66
复制
发表时间：
2017
期刊：
影响因子：
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通讯作者：
K. Balog
中科院分区：
文献类型：
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作者：
Shuo Zhang;K. Balog
我们解决了对对象（如人、博客或垂直）排序的任务，这些对象与文档不同，没有直接的基于术语的表示。为了能够将它们与关键字查询进行匹配，需要从与给定对象相关的文档中收集证据。我们提出了两种设计模式，即通用可重用检索策略，它们能够涵盖过去的大多数现有方法。一种策略在术语级别（早期融合）结合证据，而另一种策略在文档级别（晚期融合）结合证据。通过将这些模式应用于三个不同的对象检索任务：专家查找、博客提炼和垂直排序，我们展示了这些模式的通用性。
We address the task of ranking objects (such as people, blogs, or verticals) that, unlike documents, do not have direct term-based representations. To be able to match them against keyword queries, evidence needs to be amassed from documents that are associated with the given object. We present two design patterns, i.e., general reusable retrieval strategies, which are able to encompass most existing approaches from the past. One strategy combines evidence on the term level (early fusion), while the other does it on the document level (late fusion). We demonstrate the generality of these patterns by applying them to three different object retrieval tasks: expert finding, blog distillation, and vertical ranking.