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Relevance feedback and query expansion for searching the web: a model for searching a digital library

机译:搜索网络的相关性反馈和查询扩展:搜索数字图书馆的模型

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摘要

A fully operational large scale digital library is likely to be based on a distributed architecture and because of this it is likely that a number of independent search engines may be used to index different overlapping portions of the entire contents of the library. In any case, different media, text, audio, image, etc., will be indexed for retrieval by different search engines so techniques which provide a coherent and unified search over a suite of underlying independent search engines are thus likely to be an important part of navigating in a digital library. In this paper we present an architecture and a system for searching the world's largest DL, the world wide web. What makes our system novel is that we use a suite of underlying web search engines to do the bulk of the work while our system orchestrates them in a parallel fashion to provide a higher level of information retrieval functionality. Thus it is our meta search engine and not the underlying direct search engines that provide the relevance feedback and query expansion options for the user. The paper presents the design and architecture of the system which has been implemented, describes an initial version which has been operational for almost a year, and outlines the operation of the advanced version.
机译:全面运作的大规模数字图书馆可能基于分布式体系结构,因此,很可能会使用许多独立的搜索引擎来索引整个图书馆内容的不同重叠部分。无论如何,将对不同的媒体,文本,音频,图像等进行索引,以供不同的搜索引擎进行检索,因此在一系列基础独立搜索引擎上提供一致且统一的搜索的技术因此很可能是重要的一部分在数字图书馆中导航的过程。在本文中,我们提出了一种用于搜索世界上最大的DL,万维网的体系结构和系统。使我们的系统新颖的是,我们使用一组底层的Web搜索引擎来完成大部分工作,而我们的系统以并行方式编排它们以提供更高级别的信息检索功能。因此,是我们的元搜索引擎而非基础直接搜索引擎为用户提供了相关性反馈和查询扩展选项。本文介绍了已实现的系统的设计和体系结构,描述了已经运行了将近一年的初始版本,并概述了高级版本的操作。

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