A hybrid intelligent approach for the support of higher education students in literature discovery

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

Projekt

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

Zukunftsfelder FHNW

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

Komplettanzeige