Evaluation of session-based recommendation algorithms

Recommender systems help users find relevant items of interest, for example on e-commerce or media streaming sites. Most academic research is concerned with approaches that personalize the recommendations according to long-term user profiles. In many real-world applications, however, such long-term...

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Vydáno v:	User modeling and user-adapted interaction Ročník 28; číslo 4-5; s. 331 - 390
Hlavní autoři:	Ludewig, Malte, Jannach, Dietmar
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Dordrecht Springer Netherlands 01.12.2018 Springer Nature B.V
Témata:	Algorithms Computer Science Digital media Management of Computing and Information Systems Markov chains Multimedia Information Systems Neural networks Recommender systems Recurrent neural networks User Interfaces and Human Computer Interaction Sequential recommendation Deep learning Nearest neighbors Session-based recommendation Factorized Markov models
ISSN:	0924-1868, 1573-1391
On-line přístup:	Získat plný text
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