1 code implementation • LREC 2020 • Matteo Antonio Senese, Giuseppe Rizzo, Mauro Dragoni, Maurizio Morisio
In the last years, the state of the art of NLP research has made a huge step forward.
1 code implementation • 11 Oct 2018 • Diego Monti, Enrico Palumbo, Giuseppe Rizzo, Maurizio Morisio
In this paper, we present sequeval, a software tool capable of performing the offline evaluation of a recommender system designed to suggest a sequence of items.
Information Retrieval
1 code implementation • 18 Apr 2021 • Neel Kanwal, Giuseppe Rizzo
In recent years, the trend of deploying digital systems in numerous industries has hiked.
1 code implementation • 11 Oct 2018 • Diego Monti, Giuseppe Rizzo, Maurizio Morisio
For these reasons, we introduce RecLab, an open source software for evaluating recommender systems in a distributed fashion.
Information Retrieval
1 code implementation • 8 Feb 2020 • Andrea Fiandro, Giorgio Crepaldi, Diego Monti, Giuseppe Rizzo, Maurizio Morisio
This paper describes the solution of the POLINKS team to the RecSys Challenge 2019 that focuses on the task of predicting the last click-out in a session-based interaction.
1 code implementation • 15 Dec 2020 • Matteo A. Senese, Alberto Benincasa, Barbara Caputo, Giuseppe Rizzo
Our approach makes use of a neural architecture based on transformer with a multi-attentive structure that conditions the response of the agent on the request made by the user and on the product the user is referring to.
no code implementations • 27 Oct 2014 • Leon Derczynski, Diana Maynard, Giuseppe Rizzo, Marieke van Erp, Genevieve Gorrell, Raphaël Troncy, Johann Petrak, Kalina Bontcheva
Applying natural language processing for mining and intelligent information access to tweets (a form of microblog) is a challenging, emerging research area.
no code implementations • 13 Nov 2018 • Martino Mensio, Emanuele Bastianelli, Ilaria Tiddi, Giuseppe Rizzo
As the first robotic platforms slowly approach our everyday life, we can imagine a near future where service robots will be easily accessible by non-expert users through vocal interfaces.
no code implementations • SEMEVAL 2017 • Rapha{\"e}l Troncy, Enrico Palumbo, Efstratios Sygkounas, Giuseppe Rizzo
In this paper, we describe the participation of the SentiME++ system to the SemEval 2017 Task 4A {``}Sentiment Analysis in Twitter{''} that aims to classify whether English tweets are of positive, neutral or negative sentiment.
no code implementations • LREC 2014 • Giuseppe Rizzo, Marieke van Erp, Rapha{\"e}l Troncy
Detecting and classifying named entities has traditionally been taken on by the natural language processing community, whilst linking of entities to external resources, such as those in DBpedia, has been tackled by the Semantic Web community.
no code implementations • LREC 2016 • Filip Ilievski, Giuseppe Rizzo, Marieke van Erp, Julien Plu, Rapha{\"e}l Troncy
More and more knowledge bases are publicly available as linked data.
no code implementations • LREC 2016 • Marieke van Erp, Pablo Mendes, Heiko Paulheim, Filip Ilievski, Julien Plu, Giuseppe Rizzo, Joerg Waitelonis
Entity linking has become a popular task in both natural language processing and semantic web communities.
no code implementations • 2 Sep 2019 • Diego Monti, Giuseppe Rizzo, Maurizio Morisio
The public availability of collections containing user preferences is of vital importance for performing offline evaluations in the field of recommender systems.
no code implementations • JEPTALNRECITAL 2018 • Julien Plu, Kevin Cousot, Mathieu Lafourcade, Rapha{\"e}l Troncy, Giuseppe Rizzo
Entity linking systems typically rely on encyclopedic knowledge bases such as DBpedia or Freebase.