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Daniel Valcarce
Titel
Zitiert von
Zitiert von
Jahr
On the robustness and discriminative power of information retrieval metrics for top-N recommendation
D Valcarce, A Bellogín, J Parapar, P Castells
Proceedings of the 12th ACM conference on recommender systems, 260-268, 2018
992018
Assessing ranking metrics in top-N recommendation
D Valcarce, A Bellogín, J Parapar, P Castells
Information Retrieval Journal 23, 411-448, 2020
892020
Collaborative filtering embeddings for memory-based recommender systems
D Valcarce, A Landin, J Parapar, Á Barreiro
Engineering Applications of Artificial Intelligence 85, 347-356, 2019
682019
Item-based relevance modelling of recommendations for getting rid of long tail products
D Valcarce, J Parapar, Á Barreiro
Knowledge-Based Systems 103, 41-51, 2016
512016
Additive smoothing for relevance-based language modelling of recommender systems
D Valcarce, J Parapar, Á Barreiro
Proceedings of the 4th Spanish Conference on Information Retrieval, 1-8, 2016
332016
Language models for collaborative filtering neighbourhoods
D Valcarce, J Parapar, Á Barreiro
Advances in Information Retrieval: 38th European Conference on IR Research …, 2016
262016
Finding and analysing good neighbourhoods to improve collaborative filtering
D Valcarce, J Parapar, Á Barreiro
Knowledge-Based Systems 159, 193-202, 2018
252018
LiMe: Linear Methods for Pseudo-Relevance Feedback
D Valcarce, J Parapar, Á Barreiro
Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 678-687, 2018
21*2018
Exploring statistical language models for recommender systems
D Valcarce
Proceedings of the 9th ACM Conference on Recommender Systems, 375-378, 2015
192015
The Coruña corpus tool: Ten years on
A Barsaglini Castro, D Valcarce
Procesamiento del lenguaje natural, 13-19, 2020
162020
Combining top-n recommenders with metasearch algorithms
D Valcarce, J Parapar, Á Barreiro
Proceedings of the 40th International ACM SIGIR Conference on Research and …, 2017
162017
Efficient pseudo-relevance feedback methods for collaborative filtering recommendation
D Valcarce, J Parapar, Á Barreiro
Advances in Information Retrieval: 38th European Conference on IR Research …, 2016
162016
A study of smoothing methods for relevance-based language modelling of recommender systems
D Valcarce, J Parapar, Á Barreiro
Advances in Information Retrieval: 37th European Conference on IR Research …, 2015
162015
Replacing human audio with synthetic audio for on-device unspoken punctuation prediction
D Soboleva, O Skopek, M Šajgalík, V Cărbune, F Weissenberger, ...
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
132021
A study of priors for relevance-based language modelling of recommender systems
D Valcarce, J Parapar, Á Barreiro
Proceedings of the 9th ACM Conference on Recommender Systems, 237-240, 2015
132015
Axiomatic analysis of language modelling of recommender systems
D Valcarce, J Parapar, Á Barreiro
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems …, 2017
112017
A Distributed Recommendation Platform for Big Data.
D Valcarce, J Parapar, A Barreiro
J. Univers. Comput. Sci. 21 (13), 1810-1829, 2015
82015
A MapReduce implementation of posterior probability clustering and relevance models for recommendation
D Valcarce, J Parapar, Á Barreiro
Engineering Applications of Artificial Intelligence 75, 114-124, 2018
72018
When diversity met accuracy: a story of recommender systems
A Landin, E Suárez-García, D Valcarce
Proceedings 2 (18), 1178, 2018
72018
PRIN: A Probabilistic Recommender with Item Priors and Neural Models
A Landin, D Valcarce, J Parapar, Á Barreiro
52019
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