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ORCIDAlejandro Bellogín
Alejandro Bellogín Kouki
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- affiliation: Autonomous University of Madrid, Spain
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2020 – today
- 2024
[j34]Pau Muñoz, Fernando Díez, Alejandro Bellogín:
Modeling disinformation networks on Twitter: structure, behavior, and impact. Appl. Netw. Sci. 9(1): 4 (2024)- [j33]Yashar Deldjoo
, Fatemeh Nazary, Arnau Ramisa, Julian J. McAuley, Giovanni Pellegrini, Alejandro Bellogín, Tommaso Di Noia:
A Review of Modern Fashion Recommender Systems. ACM Comput. Surv. 56(4): 87:1-87:37 (2024) - [j32]Pau Muñoz, Alejandro Bellogín, Raúl Barba-Rojas, Fernando Díez:
Quantifying polarization in online political discourse. EPJ Data Sci. 13(1): 39 (2024) - [j31]Yashar Deldjoo, Dietmar Jannach, Alejandro Bellogín, Alessandro Difonzo, Dario Zanzonelli:
Fairness in recommender systems: research landscape and future directions. User Model. User Adapt. Interact. 34(1): 59-108 (2024) - [c74]Marina Alonso-Cortés, Iván Cantador, Alejandro Bellogín:
Recommendation Fairness in eParticipation: Listening to Minority, Vulnerable and NIMBY Citizens. ECIR (4) 2024: 420-436 - [c73]Alejandro Bellogín, Ludovico Boratto, Styliani Kleanthous, Elisabeth Lex, Francesca Maridina Malloci, Mirko Marras:
International Workshop on Algorithmic Bias in Search and Recommendation (BIAS). SIGIR 2024: 3033-3035 - [c72]Javier Wang, Alejandro Bellogín, Iván Cantador:
Integrating sentiment features in factorization machines: Experiments on music recommender systems. UMAP 2024: 183-188 - [c71]Miriam Fernández, Alejandro Bellogín, Iván Cantador:
Analysing the Effect of Recommendation Algorithms on the Spread of Misinformation. WebSci 2024: 159-169 - 2023
- [j30]Pablo Sánchez, Alejandro Bellogín, Ludovico Boratto:
Bias characterization, assessment, and mitigation in location-based recommender systems. Data Min. Knowl. Discov. 37(5): 1885-1929 (2023) - [j29]Enrique Amigó, Yashar Deldjoo, Stefano Mizzaro, Alejandro Bellogín:
A unifying and general account of fairness measurement in recommender systems. Inf. Process. Manag. 60(1): 103115 (2023) - [j28]Nicolás Serrano, Alejandro Bellogín:
Siamese neural networks in recommendation. Neural Comput. Appl. 35(19): 13941-13953 (2023) - [c70]Vito Walter Anelli, Daniele Malitesta, Claudio Pomo, Alejandro Bellogín, Eugenio Di Sciascio, Tommaso Di Noia:
Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis. RecSys 2023: 350-361 - [i19]Vito Walter Anelli, Daniele Malitesta, Claudio Pomo, Alejandro Bellogín, Tommaso Di Noia, Eugenio Di Sciascio:
Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis. CoRR abs/2308.00404 (2023) - [i18]Linus W. Dietz, Pablo Sánchez, Alejandro Bellogín:
Understanding the Influence of Data Characteristics on the Performance of Point-of-Interest Recommendation Algorithms. CoRR abs/2311.07229 (2023) - 2022
- [j27]Pablo Sánchez, Alejandro Bellogín:
Point-of-Interest Recommender Systems Based on Location-Based Social Networks: A Survey from an Experimental Perspective. ACM Comput. Surv. 54(11s): 223:1-223:37 (2022) - [j26]Heitor Werneck, Nícollas Silva, Adriano C. M. Pereira, Matheus Carvalho Viana, Alejandro Bellogín, Jorge Martínez Gil, Fernando Mourão, Leonardo Rocha:
A reproducible POI recommendation framework: Works mapping and benchmark evaluation. Inf. Syst. 108: 102019 (2022) - [j25]Alejandro Bellogín, Ludovico Boratto, Olga C. Santos, Liliana Ardissono, Bart P. Knijnenburg:
ACM UMAP 2022 report: 30th ACM conference on user modeling, adaptation and personalization. SIGWEB Newsl. 2022(Autumn): 1:1-1:5 (2022) - [j24]Alejandro Bellogín, Ludovico Boratto, Federica Cena:
33rd ACM conference on hypertext and social media. SIGWEB Newsl. 2022(Autumn): 2:1-2:7 (2022) - [c69]Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Francesco Maria Donini, Vincenzo Paparella, Claudio Pomo:
An Analysis of Local Explanation with LIME-RS. IIR 2022 - [c68]Vito Walter Anelli, Alejandro Bellogín, Antonio Ferrara, Daniele Malitesta, Felice Antonio Merra, Claudio Pomo, Francesco M. Donini, Eugenio Di Sciascio, Tommaso Di Noia:
The Challenging Reproducibility Task in Recommender Systems Research between Traditional and Deep Learning Models. SEBD 2022: 514-521 - [c67]Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Dietmar Jannach, Claudio Pomo:
Top-N Recommendation Algorithms: A Quest for the State-of-the-Art. UMAP 2022: 121-131 - [e3]Alejandro Bellogín, Ludovico Boratto, Federica Cena:
HT '22: 33rd ACM Conference on Hypertext and Social Media, Barcelona, Spain, 28 June 2022- 1 July 2022. ACM 2022, ISBN 978-1-4503-9233-4 [contents] - [e2]Alejandro Bellogín, Ludovico Boratto, Olga C. Santos, Liliana Ardissono, Bart P. Knijnenburg:
UMAP '22: 30th ACM Conference on User Modeling, Adaptation and Personalization, Barcelona, Spain, July 4 - 7, 2022. ACM 2022, ISBN 978-1-4503-9207-5 [contents] - [i17]Yashar Deldjoo, Fatemeh Nazary, Arnau Ramisa, Julian J. McAuley, Giovanni Pellegrini, Alejandro Bellogín, Tommaso Di Noia:
A Review of Modern Fashion Recommender Systems. CoRR abs/2202.02757 (2022) - [i16]Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Dietmar Jannach, Claudio Pomo:
Top-N Recommendation Algorithms: A Quest for the State-of-the-Art. CoRR abs/2203.01155 (2022) - [i15]Yashar Deldjoo, Dietmar Jannach, Alejandro Bellogín, Alessandro Difonzo, Dario Zanzonelli:
A Survey of Research on Fair Recommender Systems. CoRR abs/2205.11127 (2022) - 2021
- [j23]Pablo Sánchez, Alejandro Bellogín:
On the effects of aggregation strategies for different groups of users in venue recommendation. Inf. Process. Manag. 58(5): 102609 (2021) - [j22]Yashar Deldjoo, Alejandro Bellogín, Tommaso Di Noia:
Explaining recommender systems fairness and accuracy through the lens of data characteristics. Inf. Process. Manag. 58(5): 102662 (2021) - [j21]Yashar Deldjoo, Vito Walter Anelli, Hamed Zamani, Alejandro Bellogín, Tommaso Di Noia:
A flexible framework for evaluating user and item fairness in recommender systems. User Model. User Adapt. Interact. 31(3): 457-511 (2021) - [j20]Alejandro Bellogín, Alan Said:
Improving accountability in recommender systems research through reproducibility. User Model. User Adapt. Interact. 31(5): 941-977 (2021) - [c66]Vito Walter Anelli, Alejandro Bellogín, Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
MSAP: Multi-Step Adversarial Perturbations on Recommender Systems Embeddings. FLAIRS 2021 - [c65]Vito Walter Anelli, Alejandro Bellogín, Antonio Ferrara, Daniele Malitesta, Felice Antonio Merra, Claudio Pomo, Francesco Maria Donini, Eugenio Di Sciascio, Tommaso Di Noia:
How to Perform Reproducible Experiments in the ELLIOT Recommendation Framework: Data Processing, Model Selection, and Performance Evaluation. IIR 2021 - [c64]Vito Walter Anelli, Alejandro Bellogín, Antonio Ferrara, Daniele Malitesta, Felice Antonio Merra, Claudio Pomo, Francesco Maria Donini, Tommaso Di Noia:
V-Elliot: Design, Evaluate and Tune Visual Recommender Systems. RecSys 2021: 768-771 - [c63]Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Francesco Maria Donini, Vincenzo Paparella, Claudio Pomo:
Adherence and Constancy in LIME-RS Explanations for Recommendation (Long paper). KaRS/ComplexRec@RecSys 2021 - [c62]Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Claudio Pomo:
Reenvisioning the comparison between Neural Collaborative Filtering and Matrix Factorization. RecSys 2021: 521-529 - [c61]Vito Walter Anelli, Alejandro Bellogín, Antonio Ferrara, Daniele Malitesta, Felice Antonio Merra, Claudio Pomo, Francesco Maria Donini, Tommaso Di Noia:
Elliot: A Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation. SIGIR 2021: 2405-2414 - [i14]Alejandro Bellogín, Alan Said:
Improving Accountability in Recommender Systems Research Through Reproducibility. CoRR abs/2102.00482 (2021) - [i13]Vito Walter Anelli, Alejandro Bellogín, Antonio Ferrara, Daniele Malitesta, Felice Antonio Merra, Claudio Pomo, Francesco M. Donini, Tommaso Di Noia:
Elliot: a Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation. CoRR abs/2103.02590 (2021) - [i12]Miriam Fernández, Alejandro Bellogín, Iván Cantador:
Analysing the Effect of Recommendation Algorithms on the Amplification of Misinformation. CoRR abs/2103.14748 (2021) - [i11]Pablo Sánchez, Alejandro Bellogín:
Point-of-Interest Recommender Systems: A Survey from an Experimental Perspective. CoRR abs/2106.10069 (2021) - [i10]Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Claudio Pomo:
Reenvisioning Collaborative Filtering vs Matrix Factorization. CoRR abs/2107.13472 (2021) - [i9]Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Francesco Maria Donini, Vincenzo Paparella, Claudio Pomo:
Adherence and Constancy in LIME-RS Explanations for Recommendation. CoRR abs/2109.00818 (2021) - [i8]Alejandro Bellogín, Yashar Deldjoo:
Simulations for novel problems in recommendation: analyzing misinformation and data characteristics. CoRR abs/2110.04037 (2021) - 2020
- [j19]Pablo Sánchez, Alejandro Bellogín:
Time and sequence awareness in similarity metrics for recommendation. Inf. Process. Manag. 57(3): 102228 (2020) - [j18]Daniel Valcarce, Alejandro Bellogín, Javier Parapar, Pablo Castells:
Assessing ranking metrics in top-N recommendation. Inf. Retr. J. 23(4): 411-448 (2020) - [j17]Rus M. Mesas, Alejandro Bellogín:
Exploiting recommendation confidence in decision-aware recommender systems. J. Intell. Inf. Syst. 54(1): 45-78 (2020) - [j16]Pablo Sánchez, Alejandro Bellogín:
Applying reranking strategies to route recommendation using sequence-aware evaluation. User Model. User Adapt. Interact. 30(4): 659-725 (2020) - [c60]Fernando Díez, Alejandro Bellogín, Jesús Serrano:
Similitud Topológica de Usuarios: Aplicación a Los Sistemas de Recomendación. CIRCLE 2020 - [c59]María Hernández-Rubio, Alejandro Bellogín, Iván Cantador:
Aspect-based Active Learning for User Preference Elicitation in Recommender Systems. CIRCLE 2020 - [c58]Sergio Torrijos, Alejandro Bellogín:
Analysis of Co-movement Pattern Mining Methods for Recommendation. CIRCLE 2020 - [c57]Miriam Fernández, Alejandro Bellogín:
Recommender Systems and Misinformation: The Problem or the Solution? OHARS@RecSys 2020: 40-50 - [c56]Sergio Torrijos, Alejandro Bellogín, Pablo Sánchez:
Discovering Related Users in Location-based Social Networks. UMAP 2020: 353-357 - [i7]Vito Walter Anelli, Alejandro Bellogín, Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
Multi-Step Adversarial Perturbations on Recommender Systems Embeddings. CoRR abs/2010.01329 (2020)
2010 – 2019
- 2019
- [j15]Pablo Sánchez, Alejandro Bellogín:
Building user profiles based on sequences for content and collaborative filtering. Inf. Process. Manag. 56(1): 192-211 (2019) - [j14]María Hernández-Rubio, Iván Cantador, Alejandro Bellogín:
A comparative analysis of recommender systems based on item aspect opinions extracted from user reviews. User Model. User Adapt. Interact. 29(2): 381-441 (2019) - [c55]Pablo Sánchez, Alejandro Bellogín:
Attribute-based evaluation for recommender systems: incorporating user and item attributes in evaluation metrics. RecSys 2019: 378-382 - [c54]Yashar Deldjoo, Vito Walter Anelli, Hamed Zamani, Alejandro Bellogín Kouki, Tommaso Di Noia:
Recommender Systems Fairness Evaluation via Generalized Cross Entropy. RMSE@RecSys 2019 - [p3]Alejandro Bellogín, Alan Said:
Information Retrieval and Recommender Systems. Data Science in Practice 2019: 79-96 - [i6]Yashar Deldjoo, Vito Walter Anelli, Hamed Zamani, Alejandro Bellogín, Tommaso Di Noia:
Recommender Systems Fairness Evaluation via Generalized Cross Entropy. CoRR abs/1908.06708 (2019) - 2018
- [j13]Alan Said, Alejandro Bellogín:
Coherence and inconsistencies in rating behavior: estimating the magic barrier of recommender systems. User Model. User Adapt. Interact. 28(2): 97-125 (2018) - [c53]Alejandro Bellogín, Ignacio Fernández-Tobías, Iván Cantador, Paolo Tomeo:
Neighbor Selection for Cold Users in Collaborative Filtering with Positive-Only Feedback. CAEPIA 2018: 3-12 - [c52]Alejandro Bellogín, Pablo Sánchez:
Applying Subsequence Matching to Collaborative Filtering: Extended Abstract. CERI 2018: 5:1-5:2 - [c51]Pablo Sánchez, Rus M. Mesas, Alejandro Bellogín:
New approaches for evaluation: correctness and freshness: Extended Abstract. CERI 2018: 14:1-14:2 - [c50]Pablo Sánchez, Alejandro Bellogín:
Time-Aware Novelty Metrics for Recommender Systems. ECIR 2018: 357-370 - [c49]Pablo Sánchez, Alejandro Bellogín:
Challenges on Evaluating Venue Recommendation Approaches: Position Paper. RecTour@RecSys 2018: 37-40 - [c48]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 - [c47]Pablo Sánchez, Alejandro Bellogín:
Measuring anti-relevance: a study on when recommendation algorithms produce bad suggestions. RecSys 2018: 367-371 - [c46]Iván García, Alejandro Bellogín:
Towards an open, collaborative REST API for recommender systems. RecSys 2018: 504-505 - [p2]Alejandro Bellogín, Alan Said:
Offline and Online Evaluation of Recommendations. Collaborative Recommendations 2018: 295-328 - [r1]Alejandro Bellogín, Alan Said:
Recommender Systems Evaluation. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i5]Pablo Sánchez, Alejandro Bellogín:
A novel approach for venue recommendation using cross-domain techniques. CoRR abs/1809.09864 (2018) - 2017
- [j12]Alejandro Bellogín, Pablo Castells, Iván Cantador:
Statistical biases in Information Retrieval metrics for recommender systems. Inf. Retr. J. 20(6): 606-634 (2017) - [j11]Alejandro Bellogín, Pablo Sánchez:
Collaborative filtering based on subsequence matching: A new approach. Inf. Sci. 418: 432-446 (2017) - [c45]Iván Cantador, Alejandro Bellogín, María E. Cortés-Cediel, Olga Gil:
Personalized recommendations in e-participation: offline experiments for the 'Decide Madrid' platform. CitRec@RecSys 2017: 5:1-5:6 - [c44]Alejandro Bellogín, Pablo Sánchez:
Revisiting Neighbourhood-Based Recommenders For Temporal Scenarios. RecTemp@RecSys 2017: 40-44 - [c43]Rus M. Mesas, Alejandro Bellogín:
Evaluating Decision-Aware Recommender Systems. RecSys 2017: 74-78 - 2016
- [j10]Thaer Samar, Alejandro Bellogín, Arjen P. de Vries:
The strange case of reproducibility versus representativeness in contextual suggestion test collections. Inf. Retr. J. 19(3): 230-255 (2016) - [j9]Simon Dooms, Alejandro Bellogín, Toon De Pessemier, Luc Martens:
A Framework for Dataset Benchmarking and Its Application to a New Movie Rating Dataset. ACM Trans. Intell. Syst. Technol. 7(3): 41:1-41:28 (2016) - [c42]Pablo Sánchez, Alejandro Bellogín, Iván Cantador:
Studying the Effect of Data Structures on the Efficiency of Collaborative Filtering Systems. CERI 2016: 8 - 2015
- [c41]Alan Said, Alejandro Bellogín:
Replicable Evaluation of Recommender Systems. RecSys 2015: 363-364 - [c40]Thaer Samar, Alejandro Bellogín, Arjen P. de Vries:
Improving Contextual Suggestions using Open Web Domain Knowledge. SPS@SIGIR 2015: 3-9 - [i4]Alejandro Bellogín, Alan Said:
The Not-so-Magic Magic Barrier of Recommender Systems. Tiny Trans. Comput. Sci. 3 (2015) - [i3]Alan Said, Alejandro Bellogín:
Non-transparent recommender system evaluation leads to misleading results. Tiny Trans. Comput. Sci. 3 (2015) - 2014
- [j8]Alejandro Bellogín, Pablo Castells, Alan Said, Domonkos Tikk:
Report on the workshop on reproducibility and replication in recommender systems evaluation (RepSys). SIGIR Forum 48(1): 29-35 (2014) - [j7]Alejandro Bellogín, Pablo Castells, Iván Cantador:
Neighbor Selection and Weighting in User-Based Collaborative Filtering: A Performance Prediction Approach. ACM Trans. Web 8(2): 12:1-12:30 (2014) - [c39]Alan Said, Alejandro Bellogín, Jimmy Lin, Arjen P. de Vries:
Do recommendations matter?: news recommendation in real life. CSCW Companion 2014: 237-240 - [c38]Alejandro Bellogín, Thaer Samar, Arjen P. de Vries, Alan Said:
Challenges on Combining Open Web and Dataset Evaluation Results: The Case of the Contextual Suggestion Track. ECIR 2014: 430-436 - [c37]Katja Hofmann, Anne Schuth, Alejandro Bellogín, Maarten de Rijke:
Effects of Position Bias on Click-Based Recommender Evaluation. ECIR 2014: 624-630 - [c36]Alan Said, Alejandro Bellogín:
Comparative recommender system evaluation: benchmarking recommendation frameworks. RecSys 2014: 129-136 - [c35]Soude Fazeli, Babak Loni, Alejandro Bellogín, Hendrik Drachsler, Peter B. Sloep:
Implicit vs. explicit trust in social matrix factorization. RecSys 2014: 317-320 - [c34]Alan Said, Alejandro Bellogín:
Rival: a toolkit to foster reproducibility in recommender system evaluation. RecSys 2014: 371-372 - [c33]Panagiotis Adamopoulos, Alejandro Bellogín, Pablo Castells, Paolo Cremonesi, Harald Steck:
REDD 2014 - international workshop on recommender systems evaluation: dimensions and design. RecSys 2014: 393-394 - [c32]Alan Said, Alejandro Bellogín:
You are What You Eat! Tracking Health Through Recipe Interactions. RSWeb@RecSys 2014 - [c31]Thaer Samar, Arjen P. de Vries, Alejandro Bellogín:
Better Contextual Suggestions in ClueWeb12 Using Domain Knowledge Inferred from The Open Web. TREC 2014 - [c30]Alejandro Bellogín, Alan Said, Arjen P. de Vries:
The Magic Barrier of Recommender Systems - No Magic, Just Ratings. UMAP 2014: 25-36 - [i2]Alan Said, Alejandro Bellogín:
RiVal: A New Benchmarking Toolkit for Recommender Systems. ERCIM News 2014(99) (2014) - 2013
- [j6]Javier Parapar, Alejandro Bellogín, Pablo Castells, Alvaro Barreiro:
Relevance-based language modelling for recommender systems. Inf. Process. Manag. 49(4): 966-980 (2013) - [j5]Alejandro Bellogín, Jun Wang, Pablo Castells:
Bridging memory-based collaborative filtering and text retrieval. Inf. Retr. 16(6): 697-724 (2013) - [j4]Alejandro Bellogín, Iván Cantador, Pablo Castells:
A comparative study of heterogeneous item recommendations in social systems. Inf. Sci. 221: 142-169 (2013) - [j3]Alejandro Bellogín, Iván Cantador, Fernando Díez, Pablo Castells, Enrique Chavarriaga:
An empirical comparison of social, collaborative filtering, and hybrid recommenders. ACM Trans. Intell. Syst. Technol. 4(1): 14:1-14:29 (2013) - [c29]Pedro G. Campos, Alejandro Bellogín, Iván Cantador, Fernando Díez:
Time-Aware Evaluation of Methods for Identifying Active Household Members in Recommender Systems. CAEPIA 2013: 22-31 - [c28]Alan Said, Jimmy Lin, Alejandro Bellogín, Arjen P. de Vries:
A month in the life of a production news recommender system. LivingLab@CIKM 2013: 7-10 - [c27]Miguel Martinez-Alvarez, Alejandro Bellogín, Thomas Roelleke:
Document Difficulty Framework for Semi-automatic Text Classification. DaWaK 2013: 110-121 - [c26]Alejandro Bellogín, Iván Cantador, Pablo Castells, Fernando Díez:
Exploiting Social Networks in Recommendation: a Multi-Domain Comparison. DIR 2013: 40-41 - [c25]Alejandro Bellogín, Arjen P. de Vries:
Understanding Similarity Metrics in Neighbour-based Recommender Systems. ICTIR 2013: 13 - [c24]Alejandro Bellogín, Arjen P. de Vries, Jiyin He:
Artist Popularity: Do Web and Social Music Services Agree? ICWSM 2013 - [c23]Alejandro Bellogín, Javier Parapar, Pablo Castells:
Probabilistic collaborative filtering with negative cross entropy. RecSys 2013: 387-390 - [c22]Alejandro Bellogín, Pablo Castells, Alan Said, Domonkos Tikk:
Workshop on reproducibility and replication in recommender systems evaluation: RepSys. RecSys 2013: 485-486 - [c21]Alejandro Bellogín, Pablo Castells, Iván Cantador:
Improving memory-based collaborative filtering by neighbour selection based on user preference overlap. OAIR 2013: 145-148 - [c20]Alejandro Bellogín, Gebrekirstos G. Gebremeskel, Jiyin He, Alan Said, Thaer Samar, Arjen P. de Vries, Jimmy Lin, Jeroen B. P. Vuurens:
CWI and TU Delft Notebook TREC 2013: Contextual Suggestion, Federated Web Search, KBA, and Web Tracks. TREC 2013 - [c19]Iván Cantador, Ignacio Fernández-Tobías, Alejandro Bellogín:
Relating Personality Types with User Preferences in Multiple Entertainment Domains. UMAP Workshops 2013 - [c18]Alan Said, Alejandro Bellogín, Arjen P. de Vries, Benjamin Kille:
Information Retrieval and User-Centric Recommender System Evaluation. UMAP Workshops 2013 - [e1]Alejandro Bellogín, Pablo Castells, Alan Said, Domonkos Tikk:
Proceedings of the International Workshop on Reproducibility and Replication in Recommender Systems Evaluation, RepSys 2013, Hong Kong, China, October 12, 2013. ACM 2013, ISBN 978-1-4503-2465-6 [contents] - [i1]Alejandro Bellogín, Pablo Castells, Iván Cantador:
Predicting Recommender System Performance from an Information Retrieval Perspective. Tiny Trans. Comput. Sci. 2 (2013) - 2012
- [c17]Pedro G. Campos, Alejandro Bellogín, Fernando Díez, Iván Cantador:
Time feature selection for identifying active household members. CIKM 2012: 2311-2314 - [c16]Alejandro Bellogín, Javier Parapar:
Using graph partitioning techniques for neighbour selection in user-based collaborative filtering. RecSys 2012: 213-216 - 2011
- [j2]Iván Cantador, Pablo Castells, Alejandro Bellogín:
An Enhanced Semantic Layer for Hybrid Recommender Systems: Application to News Recommendation. Int. J. Semantic Web Inf. Syst. 7(1): 44-78 (2011) - [c15]Alejandro Bellogín, Jun Wang, Pablo Castells:
Structured collaborative filtering. CIKM 2011: 2257-2260 - [c14]