Business Intelligence

Based on a total of 1,590 listed non-financial firms on the Taiwan Stock Exchange and the Taipei Exchange (formerly the Over The Counter securities market) covering the period of 2007~2020, this study examines whether firm's performance on …

Creating specific datasets for machine learning models is a frequent and challenging task, requiring considerable effort in sample collection and maintaining a balanced representation of each class. In this study, our objective was to create a …

Random sample partition (RSP) is a newly developed big data representation and management model to deal with big data approximate computation problems. Academic research and practical applications have confirmed that RSP is an efficient solution …

Geldhäuser müssen den Weg der Digitalisierung weiter beschreiten, wenn sie ihren Kunden zeitgemäße Services bieten und sich auf den Einsatz von Künstlicher Intelligenz vorbereiten wollen. Dafür braucht es flexible, sichere und skalierbare Lösungen …

This chapter introduces the dynamic domain of big data analytics, illuminating its multifaceted aspects and profound significance. It commences by furnishing a comprehensive definition of big data analytics and delves into the taxonomy of this …

Collecting, processing and utilizing data information plays an increasingly important role in data warehousing/business intelligence (DWH/BI) systems. Currently, these systems are predominantly described using natural text, informal diagrams, or …

Logistik-, Operations und Supply Chain Management beschäftigen sich mit der Führung der Systeme, welche die unternehmensinterne oder -übergreifende Leistung bestimmen, sowie der Planung & Steuerung der täglichen Abläufe dazu. Diese Aufgaben werden …

The present chapter focuses on the art of web searching. Every online information should fulfil the criterion of 5 Cs—current, concise, concrete, clean and contextual. However, this seems to be a big challenge in the present era of information …