Abstract
Query suggestion, which enables the user to revise a query with a single click, has become one of the most fundamental features of Web search engines. However, it is often difficult for the user to choose from a list of query suggestions, and to understand the relation between an input query and suggested ones. In this paper, we propose a new method to present query suggestions to the user, which has been designed to help two popular query reformulation actions, namely, specialization (e.g. from "nikon" to "nikon camera") and parallel movement (e.g. from "nikon camera" to "canon camera"). Using a query log collected from a popular commercial Web search engine, our prototype called SParQS classifies query suggestions into automatically generated categories and generates a label for each category. Moreover, SParQS presents some new entities as alternatives to the original query (e.g. "canon" in response to the query "nikon"), together with their query suggestions classified in the same way as the original query's suggestions. We conducted a task-based user study to compare SParQS with a traditional "flat list" query suggestion interface. Our results show that the SParQS interface enables subjects to search more successfully than the flat list case, even though query suggestions presented were exactly the same in the two interfaces. In addition, the subjects found the query suggestions more helpful when they were presented in the SParQS interface rather than in a flat list.
| Original language | English |
|---|---|
| Title of host publication | WWW'12 - Proceedings of the 21st Annual Conference on World Wide Web |
| Pages | 389-398 |
| Number of pages | 10 |
| DOIs | |
| Publication status | Published - 2012 |
| Externally published | Yes |
| Event | 21st Annual Conference on World Wide Web, WWW'12 - Lyon Duration: 2012 Apr 16 → 2012 Apr 20 |
Other
| Other | 21st Annual Conference on World Wide Web, WWW'12 |
|---|---|
| City | Lyon |
| Period | 12/4/16 → 12/4/20 |
Fingerprint
Keywords
- Query log mining
- Query suggestion
- Search user interface
- Web search
ASJC Scopus subject areas
- Computer Networks and Communications
Cite this
Structured query suggestion for specialization and parallel movement : Effect on search behaviors. / Kato, Makoto P.; Sakai, Tetsuya; Tanaka, Katsumi.
WWW'12 - Proceedings of the 21st Annual Conference on World Wide Web. 2012. p. 389-398.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Structured query suggestion for specialization and parallel movement
T2 - Effect on search behaviors
AU - Kato, Makoto P.
AU - Sakai, Tetsuya
AU - Tanaka, Katsumi
PY - 2012
Y1 - 2012
N2 - Query suggestion, which enables the user to revise a query with a single click, has become one of the most fundamental features of Web search engines. However, it is often difficult for the user to choose from a list of query suggestions, and to understand the relation between an input query and suggested ones. In this paper, we propose a new method to present query suggestions to the user, which has been designed to help two popular query reformulation actions, namely, specialization (e.g. from "nikon" to "nikon camera") and parallel movement (e.g. from "nikon camera" to "canon camera"). Using a query log collected from a popular commercial Web search engine, our prototype called SParQS classifies query suggestions into automatically generated categories and generates a label for each category. Moreover, SParQS presents some new entities as alternatives to the original query (e.g. "canon" in response to the query "nikon"), together with their query suggestions classified in the same way as the original query's suggestions. We conducted a task-based user study to compare SParQS with a traditional "flat list" query suggestion interface. Our results show that the SParQS interface enables subjects to search more successfully than the flat list case, even though query suggestions presented were exactly the same in the two interfaces. In addition, the subjects found the query suggestions more helpful when they were presented in the SParQS interface rather than in a flat list.
AB - Query suggestion, which enables the user to revise a query with a single click, has become one of the most fundamental features of Web search engines. However, it is often difficult for the user to choose from a list of query suggestions, and to understand the relation between an input query and suggested ones. In this paper, we propose a new method to present query suggestions to the user, which has been designed to help two popular query reformulation actions, namely, specialization (e.g. from "nikon" to "nikon camera") and parallel movement (e.g. from "nikon camera" to "canon camera"). Using a query log collected from a popular commercial Web search engine, our prototype called SParQS classifies query suggestions into automatically generated categories and generates a label for each category. Moreover, SParQS presents some new entities as alternatives to the original query (e.g. "canon" in response to the query "nikon"), together with their query suggestions classified in the same way as the original query's suggestions. We conducted a task-based user study to compare SParQS with a traditional "flat list" query suggestion interface. Our results show that the SParQS interface enables subjects to search more successfully than the flat list case, even though query suggestions presented were exactly the same in the two interfaces. In addition, the subjects found the query suggestions more helpful when they were presented in the SParQS interface rather than in a flat list.
KW - Query log mining
KW - Query suggestion
KW - Search user interface
KW - Web search
UR - http://www.scopus.com/inward/record.url?scp=84860863845&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84860863845&partnerID=8YFLogxK
U2 - 10.1145/2187836.2187890
DO - 10.1145/2187836.2187890
M3 - Conference contribution
AN - SCOPUS:84860863845
SN - 9781450312295
SP - 389
EP - 398
BT - WWW'12 - Proceedings of the 21st Annual Conference on World Wide Web
ER -