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20162023
most citedPersonalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks

584 citations · 798 across the 17 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.CL2019

"The Squawk Bot": Joint Learning of Time Series and Text Data Modalities for Automated Financial Information Filtering

Xuan-Hong Dang, Syed Yousaf Shah, Petros Zerfos

Multimodal analysis that uses numerical time series and textual corpora as input data sources is becoming a promising approach, especially in the financial industry. However, the m…

cs.IR2019

A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research

Maurizio Ferrari Dacrema, Simone Boglio, Paolo Cremonesi +1

The design of algorithms that generate personalized ranked item lists is a central topic of research in the field of recommender systems. In the past few years, in particular, appr…

cs.IR2019

Towards Evaluating User Profiling Methods Based on Explicit Ratings on Item Features

Luca Luciano Costanzo, Yashar Deldjoo, Maurizio Ferrari Dacrema +2

In order to improve the accuracy of recommendations, many recommender systems nowadays use side information beyond the user rating matrix, such as item content. These systems build…

cs.IR2019

Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches

Maurizio Ferrari Dacrema, Paolo Cremonesi, Dietmar Jannach

Deep learning techniques have become the method of choice for researchers working on algorithmic aspects of recommender systems. With the strongly increased interest in machine lea…

cs.HC2019★ 15 cited

A Virtual Teaching Assistant for Personalized Learning

Luca Benedetto, Paolo Cremonesi, Manuel Parenti

In this extended abstract, we propose an intelligent system that can be used as a Personalized Virtual Teaching Assistant (PVTA) to improve the students learning experience both fo…