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ORCIDDaniel Valcarce
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2020 – today
- 2021
[c15]Daria Soboleva, Ondrej Skopek, Márius Sajgalík, Victor Carbune, Felix Weissenberger, Julia Proskurnia, Bogdan Prisacari, Daniel Valcarce
, Justin Lu, Rohit Prabhavalkar, Balint Miklos:
Replacing Human Audio with Synthetic Audio for on-Device Unspoken Punctuation Prediction. ICASSP 2021: 7653-7657- 2020
- [j10]Daniel Valcarce, Alejandro Bellogín, Javier Parapar, Pablo Castells:
Assessing ranking metrics in top-N recommendation. Inf. Retr. J. 23(4): 411-448 (2020) - [j9]Anabella Barsaglini-Castro, Daniel Valcarce:
The Coruña corpus tool: Ten years on. Proces. del Leng. Natural 64: 13-19 (2020) - [c14]Alfonso Landin, Daniel Valcarce, Javier Parapar, Álvaro Barreiro:
Shallow Neural Models for Top-N Recommendation. ECAI 2020: 2911-2912 - [i1]Daria Soboleva, Ondrej Skopek, Márius Sajgalík, Victor Carbune, Felix Weissenberger, Julia Proskurnia, Bogdan Prisacari, Daniel Valcarce, Justin Lu, Rohit Prabhavalkar, Balint Miklos:
Replacing Human Audio with Synthetic Audio for On-device Unspoken Punctuation Prediction. CoRR abs/2010.10203 (2020)
2010 – 2019
- 2019
- [j8]Daniel Valcarce, Alfonso Landin, Javier Parapar, Álvaro Barreiro:
Collaborative filtering embeddings for memory-based recommender systems. Eng. Appl. Artif. Intell. 85: 347-356 (2019) - [j7]Daniel Valcarce:
Information retrieval models for recommender systems. SIGIR Forum 53(1): 44-45 (2019) - [c13]Alfonso Landin, Daniel Valcarce, Javier Parapar, Álvaro Barreiro:
PRIN: A Probabilistic Recommender with Item Priors and Neural Models. ECIR (1) 2019: 133-147 - 2018
- [j6]Daniel Valcarce, Javier Parapar, Álvaro Barreiro:
A MapReduce implementation of posterior probability clustering and relevance models for recommendation. Eng. Appl. Artif. Intell. 75: 114-124 (2018) - [j5]Daniel Valcarce, Javier Parapar, Álvaro Barreiro:
Finding and analysing good neighbourhoods to improve collaborative filtering. Knowl. Based Syst. 159: 193-202 (2018) - [j4]Daniel Valcarce, Igo Ramalho Brilhante, José A. F. de Macêdo, Franco Maria Nardini, Raffaele Perego, Chiara Renso:
Item-driven group formation. Online Soc. Networks Media 8: 17-31 (2018) - [c12]Daniel Valcarce, Javier Parapar, Álvaro Barreiro:
Query Expansion as a Matrix Factorization Problem: Extended Abstract. CERI 2018: 3:1-3:4 - [c11]Eva Suárez-García, Alfonso Landin, Daniel Valcarce, Álvaro Barreiro:
Term Association Measures for Memory-based Recommender Systems. CERI 2018: 6:1-6:8 - [c10]Daniel Valcarce, Alejandro Bellogín, Javier Parapar, Pablo Castells:
On the robustness and discriminative power of information retrieval metrics for top-N recommendation. RecSys 2018: 260-268 - [c9]Daniel Valcarce, Javier Parapar, Álvaro Barreiro:
LiMe: linear methods for pseudo-relevance feedback. SAC 2018: 678-687 - 2017
- [j3]Daniel Valcarce, Javier Parapar, Álvaro Barreiro:
Axiomatic Analysis of Language Modelling of Recommender Systems. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 25(Supplement-2): 113-128 (2017) - [c8]Daniel Valcarce, Javier Parapar, Álvaro Barreiro:
Combining Top-N Recommenders with Metasearch Algorithms. SIGIR 2017: 805-808 - 2016
- [j2]Daniel Valcarce, Javier Parapar, Álvaro Barreiro:
Item-based relevance modelling of recommendations for getting rid of long tail products. Knowl. Based Syst. 103: 41-51 (2016) - [c7]Daniel Valcarce, Javier Parapar, Álvaro Barreiro:
Additive Smoothing for Relevance-Based Language Modelling of Recommender Systems. CERI 2016: 9 - [c6]Daniel Valcarce, Javier Parapar, Alvaro Barreiro:
Efficient Pseudo-Relevance Feedback Methods for Collaborative Filtering Recommendation. ECIR 2016: 602-613 - [c5]Daniel Valcarce, Javier Parapar, Alvaro Barreiro:
Language Models for Collaborative Filtering Neighbourhoods. ECIR 2016: 614-625 - [c4]Daniel Valcarce, Javier Parapar, Álvaro Barreiro:
Computing Neighbourhoods with Language Models in a Collaborative Filtering Scenario. IIR 2016 - 2015
- [j1]Daniel Valcarce, Javier Parapar, Alvaro Barreiro:
A Distributed Recommendation Platform for Big Data. J. Univers. Comput. Sci. 21(13): 1810-1829 (2015) - [c3]Daniel Valcarce, Javier Parapar, Alvaro Barreiro:
A Study of Smoothing Methods for Relevance-Based Language Modelling of Recommender Systems. ECIR 2015: 346-351 - [c2]Daniel Valcarce, Javier Parapar, Alvaro Barreiro:
A Study of Priors for Relevance-Based Language Modelling of Recommender Systems. RecSys 2015: 237-240 - [c1]Daniel Valcarce:
Exploring Statistical Language Models for Recommender Systems. RecSys 2015: 375-378
Coauthor Index
aka: Alvaro Barreiro
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