Paper Info
Title
The use of query auto-completion over the course of search sessions with multifaceted information needs.
Abstract
Query auto-completion (QAC) is the ubiquitous information search function that displays a list of suggested queries, where the list changes as the searcher types. This article reports on an exploratory study of QAC usage during complete search sessions in a lab study of 29 participants, where a session comprised searching on an assigned multi-faceted task. While prior research has reported average usage rates independent of the structure of search sessions, our findings are the first to describe when QAC was used within whole sessions and associations between usage and search task subtopics. Results show the value of QAC in shorter sessions and higher retrieval performance. Importantly, results also show that when QAC was used, it was most likely for the first query of a session, that use was less likely for subsequent queries, and that when the first query of a session did not use QAC, subsequent use was far less likely. The findings have implications for the value of QAC models that use knowledge from prior queries within a session to converge on optimal suggestions over successive queries. The findings are important for development of useful query assistance mechanisms for searchers. The study leads to new research questions on the effect of reformulation patterns on QAC usefulness and searchers’ attention to QAC throughout search sessions.
Year
DOI
Venue
2017
10.1016/j.ipm.2017.05.001
Information Processing & Management
Field
DocType
Volume
Data mining,World Wide Web,Information needs,Information retrieval,Computer science,Exploratory research
Journal
53
Issue
ISSN
Citations 
5
0306-4573
0
PageRank 
References 
Authors
0.34
35
3
Name
Order
Citations
PageRank
Catherine L. Smith111510.17
Jacek Gwizdka2374.11
Henry A. Feild332918.08