diff --git a/README.md b/README.md index fa316d8..5a785ed 100644 --- a/README.md +++ b/README.md @@ -15,6 +15,7 @@ It is the combined documentation for all [code repositories](https://github.com/ Informfully Recommenders is a norm-aware extension of [Cornac](https://github.com/PreferredAI/cornac). Please see the [Experiments Repository](https://github.com/Informfully/Experiments) for an overview of our past offline and online studies using this framework as back end. And see the [Online Tutorial](https://github.com/Informfully/Experiments/tree/main/experiments/tutorial) for a quick introduction on how to use this repository. +Furthermore, we provide [sample recommendations](https://github.com/Informfully/Experiments/tree/main/experiments/recsys_2025/final_recommendations) of past experiments for testing and development purposes. ![Informfully Recommenders Pipeline Overview](https://raw.githubusercontent.com/Informfully/Documentation/refs/heads/main/docs/source/uml/framework_extension_v4.2.png) @@ -39,13 +40,13 @@ It includes and supports all elements that were already part of Cornac. | Story Cluster | [Script](https://github.com/Informfully/Recommenders/blob/main/cornac/augmentation/story.py) | | Article Category | [Script](https://github.com/Informfully/Recommenders/blob/main/cornac/augmentation/category.py) | -| [Splitting](https://informfully.readthedocs.io/en/latest/splitting.html) | -|-| -| Attribute-based Sorting | -| Diversity-based Subset Construction | -| Attribute-based Stratified Splitting | -| Diversity-based Stratified Splitting | -| Clustering-based Stratified Splitting | +| [Splitting](https://informfully.readthedocs.io/en/latest/splitting.html) | Link | +|-|-| +| Attribute-based Sorting | [Link](https://github.com/Informfully/Recommenders/blob/main/cornac/eval_methods/stratified_split_diversity.py) | +| Diversity-based Subset Construction | [Link](https://github.com/Informfully/Recommenders/blob/main/cornac/eval_methods/stratified_split_diversity.py) | +| Attribute-based Stratified Splitting | [Link](https://github.com/Informfully/Recommenders/blob/main/cornac/eval_methods/stratified_split_diversity.py) | +| Diversity-based Stratified Splitting | [Link](https://github.com/Informfully/Recommenders/blob/main/cornac/eval_methods/stratified_split_diversity.py) | +| Clustering-based Stratified Splitting | [Link](https://github.com/Informfully/Recommenders/blob/main/cornac/eval_methods/stratified_split_diversity.py) | ### In-processing Stage @@ -116,10 +117,6 @@ It includes and supports all elements that were already part of Cornac. | Traditional Diversity Evaluation (Gini and ILD) | [Script](https://github.com/Informfully/Experiments/blob/main/experiments/recsys_2025/evaluation_scripts/check_diversity/check_diversity.py) | | Normative Diversity Evaluation (RADio) | [Script](https://github.com/Informfully/Experiments/tree/main/experiments/recsys_2025/evaluation_scripts/check_ntd) | -| Visualization | -| - | -| [Informfully](https://informfully.readthedocs.io/en/latest/recommendations.html) | - Item visualization is done using the [Informfully Platform](https://github.com/Informfully/Platform). Please look at the relevant documentation page for a [demo script](https://informfully.readthedocs.io/en/latest/recommendations.html). @@ -127,19 +124,21 @@ Please look at the relevant documentation page for a [demo script](https://infor If you use any code or data from this repository in a scientific publication, we ask you to cite the following papers: -- [Informfully Recommenders – A Reproducibility Framework for Diversity-aware Intra-session Recommendations](https://doi.org/10.1145/3705328.3748148), Heitz *et al.*, Proceedings of the 19th ACM Conference on Recommender Systems, 2025. +* [Informfully Recommenders – Reproducibility Framework for Diversity-aware Intra-session Recommendations](https://doi.org/10.1145/3705328.3748148), Heitz *et al.*, Proceedings of the 19th ACM Conference on Recommender Systems, 2025. ```tex @inproceedings{heitz2025recommenders, - title={Informfully Recommenders – A Reproducibility Framework for Diversity-aware Intra-session Recommendations}, + title={Informfully Recommenders – Reproducibility Framework for Diversity-aware Intra-session Recommendations}, author={Heitz, Lucien and Li, Runze and Inel, Oana and Bernstein, Abraham}, booktitle={Proceedings of the 19th ACM Conference on Recommender Systems}, pages={792--801}, year={2025}, + publisher={ACM New York, NY, USA}, + url={https://doi.org/10.1145/3705328.3748148} } ``` -- [Informfully - Research Platform for Reproducible User Studies](https://doi.org/10.1145/3640457.3688066), Heitz *et al.*, Proceedings of the 18th ACM Conference on Recommender Systems, 2024. +* [Informfully - Research Platform for Reproducible User Studies](https://doi.org/10.1145/3640457.3688066), Heitz *et al.*, Proceedings of the 18th ACM Conference on Recommender Systems, 2024. ```tex @inproceedings{heitz2024informfully, @@ -147,19 +146,23 @@ If you use any code or data from this repository in a scientific publication, we author={Heitz, Lucien and Croci, Julian A and Sachdeva, Madhav and Bernstein, Abraham}, booktitle={Proceedings of the 18th ACM Conference on Recommender Systems}, pages={660--669}, - year={2024} + year={2024}, + publisher={ACM New York, NY, USA}, + url={https://doi.org/10.1145/3640457.3688066} } ``` -- [Multi-Modal Recommender Systems: Hands-On Exploration](http://jmlr.org/papers/v21/19-805.html), Truong *et al.*, Proceedings of the 15th ACM Conference on Recommender Systems, 2021. +* [Multi-Modal Recommender Systems: Hands-On Exploration](https://doi.org/10.1145/3460231.3473324), Truong *et al.*, Proceedings of the 15th ACM Conference on Recommender Systems, 2021. ```tex @inproceedings{truong2021multi, title={Multi-modal recommender systems: Hands-on exploration}, author={Truong, Quoc-Tuan and Salah, Aghiles and Lauw, Hady}, - booktitle={Fifteenth ACM Conference on Recommender Systems}, + booktitle={Proceedings of the 15th ACM Conference on Recommender Systems}, pages={834--837}, - year={2021} + year={2021}, + publisher={ACM New York, NY, USA}, + url={https://doi.org/10.1145/3460231.3473324} } ## Contributing @@ -167,9 +170,9 @@ If you use any code or data from this repository in a scientific publication, we You are welcome to contribute to the Informfully ecosystem and become a part of our community. Feel free to: -- Fork any of the [Informfully repositories](https://github.com/Informfully/Documentation). -- Suggest new features in [Future Release](https://github.com/orgs/Informfully/projects/1). -- Make changes and create pull requests. +* Fork any of the [Informfully repositories](https://github.com/Informfully/Documentation). +* Suggest new features in [Future Release](https://github.com/orgs/Informfully/projects/1). +* Make changes and create pull requests. Please post your feature requests and bug reports in our [GitHub issues](https://github.com/Informfully/Documentation/issues) section.