Query Suggestion for Click-Absent Queries in Enterprise Search

TL;DR

This paper introduces a new method for generating query suggestions for click-absent queries in enterprise search, focusing on semantic consistency without extra resources, and demonstrates its effectiveness on real bilingual logs.

Contribution

The paper presents a novel approach specifically designed for click-absent queries, improving suggestion quality without relying on additional external data.

Findings

Effective suggestions for click-absent queries demonstrated

Method outperforms baseline approaches on enterprise logs

Semantic consistency is key to suggestion quality

Abstract

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.