Alina Beatrice Lorent

Also published as: Alina Lorenț, Alina Beatrice Lorenţ


Fixing paper assignments

  1. Please select all papers that do not belong to this person.
  2. Indicate below which author they should be assigned to.
Provide a valid ORCID iD here. This will be used to match future papers to this author.
Provide the name of the school or the university where the author has received or will receive their highest degree (e.g., Ph.D. institution for researchers, or current affiliation for students). This will be used to form the new author page ID, if needed.

TODO: "submit" and "cancel" buttons here


2018

pdf bib
The Dabblers at SemEval-2018 Task 2: Multilingual Emoji Prediction
Larisa Alexa | Alina Lorenț | Daniela Gîfu | Diana Trandabăț
Proceedings of the 12th International Workshop on Semantic Evaluation

The “Multilingual Emoji Prediction” task focuses on the ability of predicting the correspondent emoji for a certain tweet. In this paper, we investigate the relation between words and emojis. In order to do that, we used supervised machine learning (Naive Bayes) and deep learning (Recursive Neural Network).

2017

pdf bib
Wild Devs’ at SemEval-2017 Task 2: Using Neural Networks to Discover Word Similarity
Răzvan-Gabriel Rotari | Ionuț Hulub | Ștefan Oprea | Mihaela Plămadă-Onofrei | Alina Beatrice Lorenţ | Raluca Preisler | Adrian Iftene | Diana Trandabăț
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

This paper presents Wild Devs’ participation in the SemEval-2017 Task 2 “Multi-lingual and Cross-lingual Semantic Word Similarity”, which tries to automatically measure the semantic similarity between two words. The system was build using neural networks, having as input a collection of word pairs, whereas the output consists of a list of scores, from 0 to 4, corresponding to the degree of similarity between the word pairs.