Folgen
Luiz Augusto Pizzato
Luiz Augusto Pizzato
Commonwealth Bank of Australia
Bestätigte E-Mail-Adresse bei acm.org - Startseite
Titel
Zitiert von
Zitiert von
Jahr
RECON: a reciprocal recommender for online dating
L Pizzato, T Rej, T Chung, I Koprinska, J Kay
Proceedings of the fourth ACM conference on Recommender systems, 207-214, 2010
2392010
Multistakeholder recommendation: Survey and research directions
H Abdollahpouri, G Adomavicius, R Burke, I Guy, D Jannach, ...
User Modeling and User-Adapted Interaction 30, 127-158, 2020
2362020
Recommending people to people: The nature of reciprocal recommenders with a case study in online dating
L Pizzato, T Rej, J Akehurst, I Koprinska, K Yacef, J Kay
User Modeling and User-Adapted Interaction 23 (5), 447-488, 2013
1112013
CCR-A Content-Collaborative Reciprocal Recommender for Online Dating
J Akehurst, I Koprinska, K Yacef, L Pizzato, J Kay, T Rej
Proc. of the 22nd International Joint Conference on Artificial Intelligence …, 2011
822011
Reciprocal Recommender Systems: Analysis of state-of-art literature, challenges and opportunities towards social recommendation
I Palomares, C Porcel, L Pizzato, I Guy, E Herrera-Viedma
Information Fusion 69, 103-127, 2021
642021
Using Wikipedia and Conceptual Graph Structures to Generate Questions for Academic Writing Support
M Liu, RA Calvo, A Aditomo, LA Pizzato
IEEE Transactions on Learning Technologies, 2012
602012
Beyond personalization: Research directions in multistakeholder recommendation
H Abdollahpouri, G Adomavicius, R Burke, I Guy, D Jannach, ...
arXiv preprint arXiv:1905.01986, 2019
592019
Indexing on semantic roles for question answering
LA Pizzato, D Mollá
Coling 2008: Proceedings of the 2nd workshop on Information Retrieval for …, 2008
442008
Reciprocal recommenders
L Pizzato, T Rej, T Chung, K Yacef, I Koprinska, J Kay
Workshop on Intelligent Techniques for Web Personalization & Recommender …, 2010
43*2010
Pseudo relevance feedback using named entities for question answering
LA Pizzato, D Mollá, C Paris
Australasian Language Technology Workshop (ALTW2006), 83-90, 2006
402006
Finding someone you will like and who won’t reject you
LA Pizzato, T Rej, K Yacef, I Koprinska, J Kay
User Modeling, Adaption and Personalization: 19th International Conference …, 2011
372011
Scrutable user models and personalised item recommendation in mobile lifestyle applications
R Wasinger, J Wallbank, L Pizzato, J Kay, B Kummerfeld, M Böhmer, ...
User Modeling, Adaptation, and Personalization: 21th International …, 2013
342013
Explicit and implicit user preferences in online dating
J Akehurst, I Koprinska, K Yacef, L Pizzato, J Kay, T Rej
New Frontiers in Applied Data Mining - Lecture Notes in Computer Science, 15-27, 2012
332012
Learning user preferences in online dating
L Pizzato, T Chung, T Rej, I Koprinska, K Yacef, J Kay
Workshop on Preference Learning (PL-10) at the European Conference on …, 2010
282010
Stochastic matching and collaborative filtering to recommend people to people
LA Pizzato, C Silvestrini
Proceedings of the fifth ACM conference on Recommender systems, 341-344, 2011
252011
Extracting exact answers using a meta question answering system
LAS Pizzato, D Mollá-Aliod
Proceedings of the Australasian language technology workshop, 105-112, 2005
212005
Evaluation of a thesaurus-based query expansion technique
L Pizzato, V de Lima
Computational Processing of the Portuguese Language, 196-196, 2003
182003
A fairness-aware multi-stakeholder recommender system
N Ranjbar Kermany, W Zhao, J Yang, J Wu, L Pizzato
World Wide Web 24, 1995-2018, 2021
162021
An ethical multi-stakeholder recommender system based on evolutionary multi-objective optimization
NR Kermany, W Zhao, J Yang, J Wu, L Pizzato
2020 IEEE international conference on services computing (SCC), 478-480, 2020
152020
Vams 2017: Workshop on value-aware and multistakeholder recommendation
R Burke, G Adomavicius, I Guy, J Krasnodebski, L Pizzato, Y Zhang, ...
Proceedings of the Eleventh ACM Conference on Recommender Systems, 378-379, 2017
132017
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20