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Virgilijus Sakalauskas and Dalia Kriksciuniene
The growing popularity of e-commerce has prompted researchers to take a greater interest in deeper understanding online shopping behavior, consumer interest patterns, and the effectiveness of advertising campaigns. This paper presents a fresh approach fo...
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Pascal Harth, Orlando Jähde, Sophia Schneider, Nils Horn and Rüdiger Buchkremer
In this research, we present an algorithm that leverages language-transformer technologies to automate the generation of product requirements, utilizing E-Shop consumer reviews as a data source. Our methodology combines classical natural language process...
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Michail Salampasis, Alkiviadis Katsalis, Theodosios Siomos, Marina Delianidi, Dimitrios Tektonidis, Konstantinos Christantonis, Pantelis Kaplanoglou, Ifigeneia Karaveli, Chrysostomos Bourlis and Konstantinos Diamantaras
Research into session-based recommendation systems (SBSR) has attracted a lot of attention, but each study focuses on a specific class of methods. This work examines and evaluates a large range of methods, from simpler statistical co-occurrence methods t...
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Kleanthis G. Gatziolis, Nikolaos D. Tselikas and Ioannis D. Moscholios
The World Wide Web is evolving rapidly, and the Internet is now accessible to millions of users, providing them with the means to access a wealth of information, entertainment and e-commerce opportunities. Web browsing is largely impersonal and anonymous...
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Pavel Jasek, Lenka Vrana, Lucie Sperkova, Zdenek Smutny and Marek Kobulsky
This article provides an empirical statistical analysis and discussion of the predictive abilities of selected customer lifetime value (CLV) models that could be used in online shopping within e-commerce business settings. The comparison of CLV predictiv...
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