Natural language-based user guidance for knowledge graph exploration: a user study
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Autor:in (Körperschaft)
Publikationsdatum
2021
Typ der Arbeit
Studiengang
Typ
04B - Beitrag Konferenzschrift
Herausgeber:innen
Herausgeber:in (Körperschaft)
Betreuer:in
Übergeordnetes Werk
Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management
Themenheft
DOI der Originalpublikation
Link
Reihe / Serie
Reihennummer
Jahrgang / Band
1
Ausgabe / Nummer
Seiten / Dauer
95-102
Patentnummer
Verlag / Herausgebende Institution
SciTePress
Verlagsort / Veranstaltungsort
Setúbal
Auflage
Version
Programmiersprache
Abtretungsempfänger:in
Praxispartner:in/Auftraggeber:in
Zusammenfassung
Large knowledge graphs hold the promise of helping knowledge workers in their tasks by answering simple and complex questions in specialised domains. However, searching and exploring knowledge graphs in current practice still requires knowledge of certain query languages such as SPARQL or Cypher, which many untrained end users do not possess. Approaches for more user-friendly exploration have been proposed and range from natural language querying over visual cues up to query-by-example mechanisms, often enhanced with recommendation mechanisms offering guidance. We observe, however, a lack of user studies indicating which of these approaches lead to a better user experience and optimal exploration outcomes. In this work, we make a step towards closing this gap by conducting a qualitative user study with a system that relies on formulating queries in natural language and providing answers in the form of subgraph visualisations. Our system is able to offer guidance via query recommendations based on a current context. The user study evaluates the impact of this guidance in terms of both efficiency and effectiveness (recall) of user sessions. We find that both aspects are improved, especially since query recommendations provide inspiration, leading to a larger number of insights discovered in roughly the same time.
Schlagwörter
Fachgebiet (DDC)
330 - Wirtschaft
Veranstaltung
13th International Conference on Knowledge Discovery and Information Retrieval (KDIR 2021)
Startdatum der Ausstellung
Enddatum der Ausstellung
Startdatum der Konferenz
25.10.2021
Enddatum der Konferenz
27.10.2021
Datum der letzten Prüfung
ISBN
978-989-758-533-3
ISSN
Sprache
Englisch
Während FHNW Zugehörigkeit erstellt
Ja
Zukunftsfelder FHNW
Publikationsstatus
Veröffentlicht
Begutachtung
Peer-Review der ganzen Publikation
Open Access-Status
Closed
Lizenz
Zitation
WITSCHEL, Hans Friedrich, Kaspar RIESEN und Loris GRETHER, 2021. Natural language-based user guidance for knowledge graph exploration: a user study. In: Rita CUCCHIARA, Ana FRED und Joaquim FILIPE (Hrsg.), Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. Setúbal: SciTePress. 2021. S. 95–102. ISBN 978-989-758-533-3. Verfügbar unter: https://irf.fhnw.ch/handle/11654/43072