• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Information Processing & Management >Adapting Information Retrieval To Query Contexts
【24h】

Adapting Information Retrieval To Query Contexts

机译：使信息检索适应查询上下文

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In current IR approaches documents are retrieved only according to the terms specified in the query. The same answers are returned for the same query whatever the user and the search goal are. In reality, many other contextual factors strongly influence document's relevance and they should be taken into account in IR operations. This paper proposes a method, based on language modeling, to integrate several contextual factors so that document ranking will be adapted to the specific query contexts. We will consider three contextual factors in this paper: the topic domain of the query, the characteristics of the document collection, as well as context words within the query. Each contextual factor is used to generate a new query language model to specify some aspect of the information need. All these query models are then combined together to produce a more complete model for the underlying information need. Our experiments on TREC collections show that each contextual factor can positively influence the IR effectiveness and the combined model results in the highest effectiveness. This study shows that it is both beneficial and feasible to integrate more contextual factors in the current IR practice.
机译：在当前的IR方法中，仅根据查询中指定的术语来检索文档。无论用户和搜索目标是什么，都针对相同的查询返回相同的答案。实际上，许多其他上下文因素强烈影响文档的相关性，因此在IR操作中应将它们考虑在内。本文提出了一种基于语言建模的方法，该方法集成了多个上下文因素，以便文档排名将适应特定的查询上下文。在本文中，我们将考虑三个上下文因素：查询的主题领域，文档集合的特征以及查询中的上下文词。每个上下文因素都用于生成新的查询语言模型，以指定信息需求的某些方面。然后将所有这些查询模型组合在一起，以生成用于基础信息需求的更完整的模型。我们在TREC集合上的实验表明，每个上下文因素都可以对IR效果产生积极影响，并且组合的模型可以带来最高的效果。这项研究表明，将更多的上下文因素整合到当前的IR实践中既有益又可行。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号