Generating High-Quality Query Suggestion Candidates for Task-Based Search
This addresses the problem of dependency on external search engines for query suggestions in task-based search, though it appears incremental as it builds on existing pipeline approaches.
The paper tackled generating query suggestions for task-based search without relying on major search engines, focusing on a two-stage pipeline's first step, and found that three methods applied to multiple information sources produced high-quality candidates.
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.