搜索结果的个性化和协作聚类框架

D. Anastasiu, Byron J. Gao, David J. Buttler
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引用次数: 16

摘要

如何组织和呈现搜索结果在搜索引擎的实用性中起着至关重要的作用。由于网络的空前规模和搜索结果的多样性,排名列表的常用策略变得越来越不合适,聚类被认为是一种有前途的替代方法。聚类将一长串完全不同的搜索结果分成几个主题一致的聚类,允许用户通过主题导航快速定位相关结果。虽然已经提出了许多在自动聚类过程上进行创新的聚类算法,但我们介绍了ClusteringWiki,这是个性化聚类的第一个原型和框架,允许用户直接编辑聚类结果。通过Wiki界面,用户可以编辑和注释集群的成员、结构和标签,以实现个性化的表示。此外,编辑和注释可以在用户之间共享,作为改进搜索结果组织和搜索引擎效用的大规模协作方式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A framework for personalized and collaborative clustering of search results
How to organize and present search results plays a critical role in the utility of search engines. Due to the unprecedented scale of the Web and diversity of search results, the common strategy of ranked lists has become increasingly inadequate, and clustering has been considered as a promising alternative. Clustering divides a long list of disparate search results into a few topic-coherent clusters, allowing the user to quickly locate relevant results by topic navigation. While many clustering algorithms have been proposed that innovate on the automatic clustering procedure, we introduce ClusteringWiki, the first prototype and framework for personalized clustering that allows direct user editing of the clustering results. Through a Wiki interface, the user can edit and annotate the membership, structure and labels of clusters for a personalized presentation. In addition, the edits and annotations can be shared among users as a mass-collaborative way of improving search result organization and search engine utility.
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