A hybrid intelligent approach for the support of higher education students in literature discovery
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Autor:innen
Autor:in (Körperschaft)
Publikationsdatum
2022
Typ der Arbeit
Studiengang
Typ
04B - Beitrag Konferenzschrift
Herausgeber:innen
Fill, Hans-Georg
Gerber, Aurona
Lenat, Doug
Stolle, Reinhard
van Harmelen, Frank
Herausgeber:in (Körperschaft)
Betreuer:in
Übergeordnetes Werk
Proceedings of the AAAI 2022 Spring Symposium on Machine Learning and Knowledge Engineering for Hybrid Intelligence (AAAI-MAKE 2022)
Themenheft
DOI der Originalpublikation
Reihe / Serie
Reihennummer
Jahrgang / Band
Ausgabe / Nummer
Seiten / Dauer
Patentnummer
Verlag / Herausgebende Institution
Verlagsort / Veranstaltungsort
Palo Alto
Auflage
Version
Programmiersprache
Abtretungsempfänger:in
Praxispartner:in/Auftraggeber:in
Zusammenfassung
In this paper, we present a hybrid intelligent approach that combines knowledge engineering, machine learning, and human intervention to automatically recommend literature resources relevant for a high quality of literature discovery. The primary target group that we aim to support is higher education students in their first experiences with research works. The approach builds a knowledge graph by leveraging a logistic regression algorithm which is first parameterized and then influenced by the interventions of a supervisor and a student, respectively. Both interventions allow continuous learning based on both the supervisor’s preferences (e.g. high score of H-index) and the student’s feedback to the resulting literature resources. The creation of the hybrid intelligent approach followed the Design-Science Research methodology and is instantiated in a working prototype named PaperZen. The evaluation was conducted in two complementary ways: (1) by showing how the design requirements manifest in the prototype, and (2) with an illustrative scenario in which a corpus of a research project was taken as a source of truth. A small subset from the corpus was entered into the PaperZen and Google Scholar, independently. The resulting literature resources were compared with the corpus of a research project and show that PaperZen outperforms Google Scholar
Schlagwörter
Fachgebiet (DDC)
330 - Wirtschaft
Veranstaltung
AAAI 2022 Spring Symposium on Machine Learning and Knowledge Engineering for Hybrid Intelligence (AAAI-MAKE 2022)
Startdatum der Ausstellung
Enddatum der Ausstellung
Startdatum der Konferenz
21.03.2022
Enddatum der Konferenz
23.03.2022
Datum der letzten Prüfung
ISBN
ISSN
Sprache
Englisch
Während FHNW Zugehörigkeit erstellt
Ja
Publikationsstatus
Veröffentlicht
Begutachtung
Peer-Review der ganzen Publikation
Open Access-Status
Diamond
Lizenz
Zitation
PRATER, Ryan und Emanuele LAURENZI, 2022. A hybrid intelligent approach for the support of higher education students in literature discovery. In: Andreas MARTIN, Knut HINKELMANN, Hans-Georg FILL, Aurona GERBER, Doug LENAT, Reinhard STOLLE und Frank VAN HARMELEN (Hrsg.), Proceedings of the AAAI 2022 Spring Symposium on Machine Learning and Knowledge Engineering for Hybrid Intelligence (AAAI-MAKE 2022). Palo Alto. 2022. Verfügbar unter: https://doi.org/10.26041/fhnw-7307