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An exploration of ranking models and feedback method for related entity finding

机译：相关实体发现的排序模型和反馈方法的探索

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摘要

Most existing search engines focus on document retrieval. However, information needs are certainly not limited to finding relevant documents. Instead, a user may want to find relevant entities such as persons and organizations. In this paper, we study the problem of related entity finding. Our goal is to rank entities based on their relevance to a structured query, which specifies an input entity, the type of related entities and the relation between the input and related entities. We first discuss a general probabilistic framework, derive six possible retrieval models to rank the related entities, and then compare these models both analytically and empirically. To further improve performance, we study the problem of feedback in the context of related entity finding. Specifically, we propose a mixture model based feedback method that can utilize the pseudo feedback entities to estimate an enriched model for the relation between the input and related entities. Experimental results over two standard TREC collections show that the derived relation generation model combined with a relation feedback method performs better than other models.
机译：现有的大多数搜索引擎都专注于文档检索。但是，信息需求当然不仅限于查找相关文档。取而代之的是，用户可能希望找到相关的实体，例如个人和组织。在本文中，我们研究了相关实体发现的问题。我们的目标是根据实体与结构化查询的相关性对实体进行排名，结构化查询指定输入实体，相关实体的类型以及输入实体与相关实体之间的关系。我们首先讨论一个一般的概率框架，导出六个可能的检索模型来对相关实体进行排名，然后在分析和经验上对这些模型进行比较。为了进一步提高性能，我们在相关实体发现的背景下研究反馈问题。具体而言，我们提出了一种基于混合模型的反馈方法，该方法可以利用伪反馈实体来估计用于输入实体和相关实体之间关系的丰富模型。在两个标准TREC集合上的实验结果表明，与关系反馈方法相结合的导出关系生成模型的性能优于其他模型。

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  • 来源
    《Information Processing & Management》 |2013年第5期|995-1007|共13页
  • 作者

    Xitong Liu; Wei Zheng; Hui Fang;

  • 作者单位

    Department of Electrical and Computer Engineering, University of Delaware, Newark, D£ 19716, USA;

    Department of Electrical and Computer Engineering, University of Delaware, Newark, D£ 19716, USA;

    Department of Electrical and Computer Engineering, University of Delaware, Newark, D£ 19716, USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Entity retrieval; Feedback model;

    机译：实体检索;反馈模型;

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