Event-centric Query Suggestion for Online News
Sachin, Dhaval Patel

TL;DR
This paper introduces a novel event-centric query suggestion method for online news that leverages news article metadata to improve relevance, especially for less popular or emerging events, outperforming existing search engines.
Contribution
It proposes a new approach using news article metadata for query suggestions, addressing limitations of log-based methods in capturing emerging and less popular news events.
Findings
Outperforms Google News, Bing News, Google Search, and Bing Search in relevance.
Effectively captures emerging and less popular events.
Provides more timely and event-specific query suggestions.
Abstract
Query suggestion refers to the task of suggesting relevant and related queries to a search engine user to help in query formulation process and to expedite information retrieval with minimum amount of effort. It is highly useful in situations where the search requirements are not well understood and hence it has been widely adopted by search engines to guide users' search activity. For news websites, user queries have a time sensitive nature inherent in them. When some new event happens, there is a sudden burst in queries related to that event and such queries are sustained over a period of time before fading away with that event. In addition to this temporal aspect of search queries fired at news websites, they have an addition distinct quality, i.e., they are intended to get event related information majority of the times. Existing work on generating query suggestions involves…
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Taxonomy
TopicsWeb Data Mining and Analysis · Complex Network Analysis Techniques · Advanced Image and Video Retrieval Techniques
