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arXiv · 1802.07997

Generating High-Quality Query Suggestion Candidates for Task-Based Search

Heng Ding·Shuo Zhang·Darío Garigliotti·Krisztian Balog
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Abstract

We address the task of generating query suggestions for task-based search. The current state of the art relies heavily on suggestions provided by a major search engine. In this paper, we solve the task without reliance on search engines. Specifically, we focus on the first step of a two-stage pipeline approach, which is dedicated to the generation of query suggestion candidates. We present three methods for generating candidate suggestions and apply them on multiple information sources. Using a purpose-built test collection, we find that these methods are able to generate high-quality suggestion candidates.

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Heng Ding, Shuo Zhang, Darío Garigliotti, Krisztian Balog. 2018-02-22. Generating High-Quality Query Suggestion Candidates for Task-Based Search. https://doi.org/10.1007/978-3-319-76941-7_54

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