Artificial Intelligence for Online Review Platforms - Data Understanding, Enhanced Approaches and Explanations in Recommender Systems and Aspect-based Sentiment Analysis - University of Regensburg Publication Server

Item type:	Thesis of the University of Regensburg (PhD)
Open Access Type:	Primary Publication
Date:	25 August 2022
Referee:	Prof. Dr. Bernd Heinrich
Date of exam:	7 July 2022
Institutions:	Business, Economics and Information Systems > Institut für Wirtschaftsinformatik > Lehrstuhl für Wirtschaftsinformatik II (Prof. Dr. Bernd Heinrich) Informatics and Data Science > Department Information Systems > Lehrstuhl für Wirtschaftsinformatik II (Prof. Dr. Bernd Heinrich)
Keywords:	artificial intelligence, online consumer reviews, data understanding, enhanced approaches, explanations, recommender systems, aspect-based sentiment analysis
Dewey Decimal Classification:	000 Computer science, information & general works > 004 Computer science 300 Social sciences > 330 Economics 600 Technology > 600 Technology (Applied sciences)
Status:	Published
Refereed:	Yes, this version has been refereed
Created at the University of Regensburg:	Yes
Item ID:	52707

Abstract (English)

The epoch-making and ever faster technological progress provokes disruptive changes and poses pivotal challenges for individuals and organizations. In particular, artificial intelligence (AI) is a disruptive technology that offers tremendous potential for many fields such as information systems and electronic commerce. Therefore, this dissertation contributes to AI for online review platforms ...

Abstract (English)

The epoch-making and ever faster technological progress provokes disruptive changes and poses pivotal challenges for individuals and organizations. In particular, artificial intelligence (AI) is a disruptive technology that offers tremendous potential for many fields such as information systems and electronic commerce. Therefore, this dissertation contributes to AI for online review platforms aiming at enabling the future for consumers, businesses and platforms by unveiling the potential of AI. To achieve this goal, the dissertation investigates six major research questions embedded in the triad of data understanding of online consumer reviews, enhanced approaches and explanations in recommender systems and aspect-based sentiment analysis.

Translation of the abstract (German)

Der epochale und immer schnellere technologische Fortschritt führt zu disruptiven Veränderungen und stellt zentrale Herausforderungen für Individuen und Organisationen. Insbesondere Artificial Intelligence (AI) stellt eine disruptive Technologie dar, die enormes Potenzial für viele Bereiche wie Information Systems oder Electronic Commerce bietet. Deshalb leistet diese Dissertation einen Beitrag ...

Translation of the abstract (German)

Der epochale und immer schnellere technologische Fortschritt führt zu disruptiven Veränderungen und stellt zentrale Herausforderungen für Individuen und Organisationen. Insbesondere Artificial Intelligence (AI) stellt eine disruptive Technologie dar, die enormes Potenzial für viele Bereiche wie Information Systems oder Electronic Commerce bietet. Deshalb leistet diese Dissertation einen Beitrag zu AI für Online Review Plattformen um die Zukunft für Kunden, Unternehmen und Plattformen zu ermöglichen durch das Freisetzen des Potenzials von AI. Um dieses Ziel zu erreichen untersucht die Dissertation sechs zentrale Forschungsfragen welche in den Dreiklang von Datenverständnis von Online Consumer Reviews, Erweiterten Ansätzen und Erklärungen bei Recommender Systemen und Aspekt-basierter Sentimentanalyse.

Artificial Intelligence for Online Review Platforms - Data Understanding, Enhanced Approaches and Explanations in Recommender Systems and Aspect-based Sentiment Analysis

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Abstract (English)

Abstract (English)

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Translation of the abstract (German)

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