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20112026
most citedSemantic Matchmaking as Non-Monotonic Reasoning: A Description Logic Approach

117 citations · 658 across the 80 of their papers we have counts for

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Showing 2024Show all

13 papers · 1 filter

cs.IR2024

DataRec: A Python Library for Standardized and Reproducible Data Management in Recommender Systems

Alberto Carlo Maria Mancino, Salvatore Bufi, Angela Di Fazio +4

Recommender systems have demonstrated significant impact across diverse domains, yet ensuring the reproducibility of experimental findings remains a persistent challenge. A primary…

cs.CV2024

Scalable Cloud-Native Pipeline for Efficient 3D Model Reconstruction from Monocular Smartphone Images

Potito Aghilar, Vito Walter Anelli, Michelantonio Trizio +1

In recent years, 3D models have gained popularity in various fields, including entertainment, manufacturing, and simulation. However, manually creating these models can be a time-c…

cs.IR2024

Fashion Image-to-Image Translation for Complementary Item Retrieval

Matteo Attimonelli, Claudio Pomo, Dietmar Jannach +1

The increasing demand for online fashion retail has boosted research in fashion compatibility modeling and item retrieval, focusing on matching user queries (textual descriptions o…

cs.IR2024★ 1 cited

Dot Product is All You Need: Bridging the Gap Between Item Recommendation and Link Prediction

Daniele Malitesta, Alberto Carlo Maria Mancino, Pasquale Minervini +1

Item recommendation (the task of predicting if a user may interact with new items from the catalogue in a recommendation system) and link prediction (the task of identifying missin…

cs.IR2024★ 8 cited

Enhancing Sequential Music Recommendation with Personalized Popularity Awareness

Davide Abbattista, Vito Walter Anelli, Tommaso Di Noia +2

In the realm of music recommendation, sequential recommender systems have shown promise in capturing the dynamic nature of music consumption. Nevertheless, traditional Transformer-…

cs.IR2024★ 2 cited

Large-scale Benchmarks for Multimodal Recommendation with Ducho

Matteo Attimonelli, Danilo Danese, Angela Di Fazio +3

The common multimodal recommendation pipeline involves (i) extracting multimodal features, (ii) refining their high-level representations to suit the recommendation task, (iii) opt…