丰富新闻文章与相关的搜索查询

David Carmel, Yaroslav Fyodorov, Saar Kuzi, Avihai Mejer, Fiana Raiber, Elad Rainshmidt
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引用次数: 1

摘要

使用辅助资源丰富新闻文章的内容是在线新闻服务经常采用的一种技术,以保持文章的最新状态,从而增加用户的参与度。我们解决了用相关搜索查询丰富新闻文章的任务,这些查询是从搜索引擎的查询日志中提取的。单击推荐查询将调用一个搜索会话,允许用户进一步探索与文章相关的内容。我们提出了一个用于查询推荐的三阶段检索框架,该框架包含各种文章相关和文章无关的相关信号。基于由专业编辑使用注释进行的离线实验和由真实用户进行的大规模在线实验的评估,证明了我们的方法的优点。此外,对我们在线实验的全面分析揭示了用户倾向于点击的查询类型的有趣特征,以及他们与搜索引擎结果页面的交互性质。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enriching News Articles with Related Search Queries
Enriching the content of news articles with auxiliary resources is a technique often employed by online news services to keep articles up-to-date and thereby increase users' engagement. We address the task of enriching news articles with related search queries, which are extracted from a search engine's query log. Clicking on a recommended query invokes a search session that allows the user to further explore content related to the article. We present a three-phase retrieval framework for query recommendation that incorporates various article-dependent and article-independent relevance signals. Evaluation based on an offline experiment, performed using annotations by professional editors, and a large-scale online experiment, conducted with real users, demonstrates the merits of our approach. In addition, a comprehensive analysis of our online experiment reveals interesting characteristics of the type of queries users tend to click and the nature of their interaction with the resultant search engine results page.
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