Abstract
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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