There are no reviews yet. Be the first to send feedback to the community and the maintainers!
elliot
Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluationadversarial-recommender-systems-survey
The goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show another successful application of AML in generative adversarial networks (GANs) for generative applications, thanks to their ability for learning (high-dimensional) data distributions. In this survey, we provide an exhaustive literature review of 74 articles published in major RS and ML journals and conferences. This review serves as a reference for the RS community, working on the security of RS or on generative models using GANs to improve their quality.LODrecsys-datasets
Here, we provide mappings to DBpedia resources of items in well known datasets to evaluate recommender systems. This can allows practitioners in the field to evaluate and compare their algorithms with existing approaches.amlrecsys-tutorial
Tutorial by Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia and Felice Antonio Merra about Adversarial Machine Learning in Recommender SystemsKGFlex
Official implementation of the paper "Sparse Feature Factorization for Recommender Systems with Knowledge Graphs"Reenvisioning-the-comparison-between-Neural-Collaborative-Filtering-and-Matrix-Factorization
lodreclib
lodreclib is a Java library to build recommendation engines which exploit the information encoded in Linked (Open) Data datasets.recsys2021-pursuing-privacy
Material supporting the tutorial "Pursuing Privacy in Recommender Systems: The View of Users and Researchers from Regulations to Applications" held at the 15th ACM Conference on Recommender Systems in Amsterdam, NetherlandsSEMAUTO-2.0
Semantics-Aware Autoencoder Neural NetworkFedBPR
Official implementation of the papers "User-controlled federated matrix factorization for recommender systems" and "FedeRank: User Controlled Feedback with Federated Recommender Systems"Graph-RSs-Reproducibility
Accepted as reproducibility paper at RecSys 2023.LoG-2023-GNNs-RecSys
Presented as tutorial at the Second Learning on Graphs Conference (LoG 2023)HandsOn-ECIR2021
SEMAUTO
A Java framework to build semantics-aware autoencoder neural network from a knowledge-graph.Ducho
Python framework to extract multimodal features for multimodal recommendation in a highly-customizable way.Agent-Based-Artificial-Intelligence
Codes for hands-on lessonsRecommender-ChatGPT
The official source code and datasets for the paper titled "Evaluating ChatGPT as a Recommender System: A Rigorous Approach"Formal-MultiMod-Rec
Formalizing Multimedia Recommendation through Multimodal Deep Learning, accepted in ACM Transactions on Recommender Systems.Top-N-Recommendation-Algorithms-A-Quest-for-the-State-of-the-Art
This is the official repository of the paper Top-N Recommendation Algorithms: A Quest for the State of the Artinteractive-question-answering-systems-survey
A collection of work regarding Interactive Question Answering System standing over 10 years.LinkedDatasets
KGTORe
Official implementation of the paper "KG-TORE: Tailored recommendations through knowledge-aware GNN models" accepted at RecSys 2023Visual-Adversarial-Recommendation
we present an evaluation framework, named Visual Adversarial Recommender (\var), to empirically investigate the performance of defended or undefended DNNs in various visually-aware item recommendation tasks.Multimodal-Feature-Extractor
A Python implementation to extract multimodal features (visual and textual).Content-Style-VRSs
Official implementation of the paper "Leveraging Content-Style Item Representation for Visual Recommendation" accepted at ECIR 2022losm
Linked Open Street Map - a middleware to query OSM via SPARQL queriesTimePOP
TimePop is a simple and efficient algorithm that combines the notion of personalized popularity and temporal aspects.Augmented-and-Linked-Open-Datasets-for-Recommendation
Interpretability-of-BERT-Latent-Space-through-Knowledge-Graphs
Here we present the code we implemented to interpret and explain the BERT language model through the latent space it generates. The work identifies a feasibility study of analyzing BERT's latent semantic space using a knowledge graph.MultiMod-Popularity-Bias
Accepted as full paper at MMIR @ ACM Multimedia 2023dlpreferences
Reasoning with preferences in Description Logicssimlib
A Java framework for semantic similarity and relatedness metrics for Knowledge GraphsDatasetsSplits
This is a collection of splittings of publicly available Datasets. This collection has been created for two main purposes:iir2021
IIR 2021 | 11th Italian Information Retrieval WorkshopClientAware-FL
TAaMR
Targeted Adversarial Attack against Multimedia Recommender Systems (TAaMR) at DSML2020The-importance-of-being-dissimilar-in-Recommendation
Similarity measures play a fundamental role in memory-based nearest neighbors approaches. They recommend items to a user based on the similarity of either items or users in a neighborhood. In this paper we argue that, although it keeps a leading importance in computing recommendations, similarity between users or items should be paired with a value of dissimilarity (computed not just as the complement of the similarity one). We formally modeled and injected this notion in some of the most used similarity measures and evaluated our approach showing its effectiveness in terms of accuracy results.KGUF
Graph-Characteristics
qalib
HybridFactorizationMachines
Edge-Graph-Collaborative-Filtering
Accepted as full paper at DL4SR@CIKM2022SAC2017
Code and results for the paper : "Schema-summarization in Linked-Data-based feature selection for recommender systems"CNNs-in-VRSs
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshopspoldo
A tool for exposing the deep Web in the Linked Data cloudanna
Vocal Assistant / Chatbot Anna to explore Puglia Digital LibraryMSAP
In this work, we extend the FGSM method proposing multistep adversarial perturbation (MSAP) procedures to study the recommendersโ robustness under powerful methods. Letting fixed the perturbation magnitude, we illustrate that MSAP is much more harmful than FGSM in corrupting the recommendation performance of BPR-MF.DIVAN
ECIR2023-Graph-CF
Accepted as full paper at ECIR 2023X-LOD-Lookup
RecMOE
A library to compute Pareto fronts and evaluate them using Quality Indicators (QIs) for Recommender Systemsfondamenti-web-2023-2024
Soluzioni complete per le esercitazioni di Fondamenti del WebFeatures-Factorization
Features-Factorization and Feature Spreading Relevance (Knowledge-aware Recommender Systems)The-Idiosyncratic-Effects-of-Adversarial-Training
Code and Data for the #RecSys2021 article "The Idiosyncratic Effects of Adversarial Training on Bias in Personalized Recommendation Learning".LHider
Topology-Graph-Collaborative-Filtering
Perceptual-Rec-Mutation-of-Adv-VRs
Accepted at WDSC@NeurIPS2020Graph-Demo
Accepted as demo paper at UMAP 2023ISWC2017
X-LOD
A Content Management System to edit and publish your Linked Open Data. X-LOD has been inspired by the Wikidata project with RDF data and triplestores in mind.Ducho-meets-Elliot
Multimodal-RSs-Reproducibility
poldo-client
MultiModal-Eval
Accepted as full paper at EvalRS@KDD2023Love Open Source and this site? Check out how you can help us