Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | CHIIR 2019 |
| Untertitel | Proceedings of the 2019 Conference on Human Information Interaction and Retrieval |
| Erscheinungsort | New York |
| Herausgeber (Verlag) | Association for Computing Machinery (ACM) |
| Seiten | 331-335 |
| Seitenumfang | 5 |
| ISBN (elektronisch) | 9781450360258 |
| Publikationsstatus | Veröffentlicht - 8 März 2019 |
| Veranstaltung | CHIIR 2019: ACM SIGIR Conference in Human Information Interaction and Retrieval - Glasgow, Großbritannien / Vereinigtes Königreich Dauer: 10 März 2019 → 14 März 2019 |
Abstract
Queries containing false memories (i.e., attributes the user misremembered about a searched item) represent a challenge for search systems. A query with a false memory will match inadequate results or even no result, and an automatic query correction is necessary to satisfy the user expectations. For voice-based search interfaces, which aim at a natural, dialog-based search experience, a sensible answer to this kind of unintentionally ill-posed queries is even more crucial. However, the usual solutions in display-based interfaces for queries without matches (e.g., suggesting to drop some query terms) cannot really be transferred to the voice-based setting. Based on the assumption that false memory queries could be identified-a research problem in its own right-, we present the first user study on how voice-based search systems may communicate the respective corrections to a user. Our study compares the user satisfaction in a voice-based search setting for three kinds of false memory clarifications and a baseline case where the system just answers “I don't know.” Our findings suggest that (1) users are more satisfied when they receive a clarification that and how the system corrected a false memory, (2) users even prefer failed correction attempts over no such attempt, and (3) the tone of the clarification has to be considered for the best possible user satisfaction as well.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Mensch-Maschine-Interaktion
- Informatik (insg.)
- Information systems
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CHIIR 2019: Proceedings of the 2019 Conference on Human Information Interaction and Retrieval. New York: Association for Computing Machinery (ACM), 2019. S. 331-335.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Clarifying false memories in voice-based search
AU - Kiesel, Johannes
AU - Bahrami, Arefeh
AU - Stein, Benno
AU - Anand, Avishek
AU - Hagen, Matthias
PY - 2019/3/8
Y1 - 2019/3/8
N2 - Queries containing false memories (i.e., attributes the user misremembered about a searched item) represent a challenge for search systems. A query with a false memory will match inadequate results or even no result, and an automatic query correction is necessary to satisfy the user expectations. For voice-based search interfaces, which aim at a natural, dialog-based search experience, a sensible answer to this kind of unintentionally ill-posed queries is even more crucial. However, the usual solutions in display-based interfaces for queries without matches (e.g., suggesting to drop some query terms) cannot really be transferred to the voice-based setting. Based on the assumption that false memory queries could be identified-a research problem in its own right-, we present the first user study on how voice-based search systems may communicate the respective corrections to a user. Our study compares the user satisfaction in a voice-based search setting for three kinds of false memory clarifications and a baseline case where the system just answers “I don't know.” Our findings suggest that (1) users are more satisfied when they receive a clarification that and how the system corrected a false memory, (2) users even prefer failed correction attempts over no such attempt, and (3) the tone of the clarification has to be considered for the best possible user satisfaction as well.
AB - Queries containing false memories (i.e., attributes the user misremembered about a searched item) represent a challenge for search systems. A query with a false memory will match inadequate results or even no result, and an automatic query correction is necessary to satisfy the user expectations. For voice-based search interfaces, which aim at a natural, dialog-based search experience, a sensible answer to this kind of unintentionally ill-posed queries is even more crucial. However, the usual solutions in display-based interfaces for queries without matches (e.g., suggesting to drop some query terms) cannot really be transferred to the voice-based setting. Based on the assumption that false memory queries could be identified-a research problem in its own right-, we present the first user study on how voice-based search systems may communicate the respective corrections to a user. Our study compares the user satisfaction in a voice-based search setting for three kinds of false memory clarifications and a baseline case where the system just answers “I don't know.” Our findings suggest that (1) users are more satisfied when they receive a clarification that and how the system corrected a false memory, (2) users even prefer failed correction attempts over no such attempt, and (3) the tone of the clarification has to be considered for the best possible user satisfaction as well.
UR - http://www.scopus.com/inward/record.url?scp=85063154197&partnerID=8YFLogxK
U2 - 10.1145/3295750.3298961
DO - 10.1145/3295750.3298961
M3 - Conference contribution
AN - SCOPUS:85063154197
SP - 331
EP - 335
BT - CHIIR 2019
PB - Association for Computing Machinery (ACM)
CY - New York
T2 - CHIIR 2019
Y2 - 10 March 2019 through 14 March 2019
ER -