Explanation mining: Post hoc interpretability of latent factor models for recommendation systems
G Peake, J Wang - Proceedings of the 24th ACM SIGKDD International …, 2018 - dl.acm.org
The widescale use of machine learning algorithms to drive decision-making has highlighted
the critical importance of ensuring the interpretability of such models in order to engender …
the critical importance of ensuring the interpretability of such models in order to engender …
Scalable and interpretable product recommendations via overlapping co-clustering
We consider the problem of generating interpretable recommendations by identifying
overlapping co-clusters of clients and products, based only on positive or implicit feedback …
overlapping co-clusters of clients and products, based only on positive or implicit feedback …
Addressing interpretability and cold-start in matrix factorization for recommender systems
We consider the problem of generating interpretable recommendations by identifying
overlapping co-clusters of clients and products, based only on positive or implicit feedback …
overlapping co-clusters of clients and products, based only on positive or implicit feedback …
Designing a multichannel nanocavity coupled photonic crystal biosensor for detection of glucose concentration in blood
S Ameta, A Sharma, PK Inaniya - 2017 8th international …, 2017 - ieeexplore.ieee.org
Biosensor is an analytical device used to detect the biological analyte, which can be
antibodies enzymes cells or biomolecules. Biosensors have many applications like in …
antibodies enzymes cells or biomolecules. Biosensors have many applications like in …
Matrix factorization and contrast analysis techniques for recommendation
M Aleksandrova - 2017 - theses.hal.science
In many application areas, data elements can be high-dimensional. This raises the problem
of dimensionality reduction. The dimensionality reduction techniques can be classified …
of dimensionality reduction. The dimensionality reduction techniques can be classified …
Exploring current viewing context for tv contents recommendation
M Bambia, M Boughanem, R Faiz - 2016 IEEE/WIC/ACM …, 2016 - ieeexplore.ieee.org
Due to the diversity of alternative programs to watch and the change of viewers' contexts,
real-time prediction of viewers' preferences in certain circumstances becomes increasingly …
real-time prediction of viewers' preferences in certain circumstances becomes increasingly …
High-performance recommender system training using co-clustering on CPU/GPU clusters
Recommender systems are becoming the crystal ball of the Internet because they can
anticipate what the users may want, even before the users know they want it. However, the …
anticipate what the users may want, even before the users know they want it. However, the …
Recommender systems using temporal restricted sequential patterns
AP Galarreta, H Samamé, Y Maehara… - Journal of Ambient …, 2023 - Springer
Recommendation systems are algorithms for suggesting relevant items to users. Generally,
the recommendations are expressed in what will be recommended and a value representing …
the recommendations are expressed in what will be recommended and a value representing …
Jointly integrating current context and social influence for improving recommendation
M Bambia - 2017 - theses.hal.science
Due to the diversity of alternative contents to choose and the change of users' preferences,
real-time prediction of users' preferences in certain users' circumstances becomes …
real-time prediction of users' preferences in certain users' circumstances becomes …