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SEARCH ENGINE DEVELOPMENT USING EVOLUTIONARY COMPUTATION METHODOLOGIES

机译:使用进化计算方法搜索引擎

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摘要

Early search engines had their origin in information retrieval systems. These systems were typically developed by human editors to index a document set that was static over long periods of time. The information retrieval systems provided a stable user environment that was eventually optimized over time and facilitative of incremental growth in the document collection. Early search engines used this tried and tested information retrieval model, but encountered usability limitations when the document growth rate accelerated. The limitations of the model became magnified as the need for automated indexing mechanisms grew, and information retrieval systems began to be used with dynamic document datasets. These limitations are still apparent in current search engines which incorporate aspects of these early information retrieval systems. This chapter presents the Tocorime Apicu approach for replacing the information retrieval model with an information sharing model that adapts to changing conditions within the Internet using the stochastic optimization methodologies of evolutionary computation. Experimental results are presented.
机译:早期的搜索引擎起源于信息检索系统。这些系统通常是由人类编辑人员开发的,用于对长时间处于静态的文档集建立索引。信息检索系统提供了一个稳定的用户环境,该环境最终会随着时间的流逝而得到优化,并有助于文档收集中的增量增长。早期的搜索引擎使用了这种久经考验的信息检索模型,但是当文档增长速度加快时遇到了可用性限制。随着对自动索引机制的需求的增长,该模型的局限性日益扩大,并且信息检索系统开始与动态文档数据集一起使用。这些限制在结合了这些早期信息检索系统各方面的当前搜索引擎中仍然显而易见。本章介绍了Tocorime Apicu方法,该方法通过使用进化计算的随机优化方法来适应信息变化的信息共享模型,以信息共享模型代替信息检索模型。给出实验结果。

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