Query Suggestion for Click-Absent Queries in Enterprise Search
This addresses a specific issue for enterprise search users by improving suggestions for queries without click data, though it is incremental as it builds on existing query suggestion methods.
The paper tackles the problem of generating query suggestions for click-absent queries in enterprise search, proposing a method that ensures semantic consistency without additional resources, and shows it generates comparatively good suggestions on a real bilingual search log.
Creating alternative queries, also known as query suggestion, has been proved to be helpful on improving users' search experience. Owing to the suggestions, users could retrieve their information need more quickly and accurately. In many scenarios, these suggestions could be generated from the click-through logs by establishing a bipartite graph of the clicked query-document pairs. Most of the existing methods focused on click-existing queries which possess clicked information in the search logs, to suggest related queries using the co-clicked documents. In this paper, we propose a simple yet effective query suggestion method particularly for click-absent queries by ensuring semantic consistency without utilising any additional resources. Our experimental results show that the proposed technique generates comparatively good suggestions for click-absent queries on a real bilingual enterprise search log.