机译:重新研究基于集群的范例以实现隐式搜索结果的多样化
Faculty of Library, Information and Media Science, University of Tsukuba;
Department of Social Informatics, Graduate School of Informatics, Kyoto University;
IRLab, Computer Science Department, University of A Coruña;
Research Center for Knowledge Communities, Faculty of Library, Information and Media Science, University of Tsukuba;
School of Computing Science, University of Glasgow;
School of Computing Science, University of Glasgow;
School of Computing Science, University of Glasgow;
Cluster-based IR; Implicit SRD; Integer linear programming; Affinity propagation;
机译:基于均值方差分析的联合搜索中搜索结果多样化方法
机译:隐性视觉搜索:重新介绍引导搜索范式
机译:低成本,自下而上的评估措施,用于评估搜索结果多样化
机译:预测隐式Web搜索结果多样化的候选文档集的大小
机译:元搜索引擎中的自动搜索界面聚类和搜索结果处理
机译:Root Broverting Revisited:强制对根部吸取的范例 - 是一个范式班次所需的以便更多地了解这一现象?
机译:重新审视基于群集的范例,用于隐式搜索结果多样化
机译:利用本体搜索结果多样化。