Search Results for author: Erion Çano

Found 14 papers, 2 papers with code

How Many Pages? Paper Length Prediction from the Metadata

1 code implementation29 Oct 2020 Erion Çano, Ondřej Bojar

Being able to predict the length of a scientific paper may be helpful in numerous situations.

A Data-driven Neural Network Architecture for Sentiment Analysis

no code implementations30 Jun 2020 Erion Çano, Maurizio Morisio

Our results indicate that parallel convolutions of filter lengths up to three are usually enough for capturing relevant text features.

Sentiment Analysis

Mood-based On-Car Music Recommendations

no code implementations25 Jun 2020 Erion Çano, Riccardo Coppola, Eleonora Gargiulo, Marco Marengo, Maurizio Morisio

Driving and music listening are two inseparable everyday activities for millions of people today in the world.

Recommendation Systems

Automating Text Naturalness Evaluation of NLG Systems

no code implementations23 Jun 2020 Erion Çano, Ondřej Bojar

Instead of relying on human participants for scoring or labeling the text samples, we propose to automate the process by using a human likeliness metric we define and a discrimination procedure based on large pretrained language models with their probability distributions.

Text Generation

Human or Machine: Automating Human Likeliness Evaluation of NLG Texts

no code implementations5 Jun 2020 Erion Çano, Ondřej Bojar

Automatic evaluation of various text quality criteria produced by data-driven intelligent methods is very common and useful because it is cheap, fast, and usually yields repeatable results.

Text Generation

Quality of Word Embeddings on Sentiment Analysis Tasks

no code implementations6 Mar 2020 Erion Çano, Maurizio Morisio

Quality of word embeddings and performance of their applications depends on several factors like training method, corpus size and relevance etc.

Machine Translation Sentiment Analysis +1

Two Huge Title and Keyword Generation Corpora of Research Articles

no code implementations11 Feb 2020 Erion Çano, Ondřej Bojar

Recent developments in sequence-to-sequence learning with neural networks have considerably improved the quality of automatically generated text summaries and document keywords, stipulating the need for even bigger training corpora.

Text Summarization

Keyphrase Generation: A Multi-Aspect Survey

no code implementations11 Oct 2019 Erion Çano, Ondřej Bojar

In this survey, we examine various aspects of the extractive keyphrase generation methods and focus mostly on the more recent abstractive methods that are based on neural networks.

Text Summarization

Efficiency Metrics for Data-Driven Models: A Text Summarization Case Study

no code implementations14 Sep 2019 Erion Çano, Ondřej Bojar

Using data-driven models for solving text summarization or similar tasks has become very common in the last years.

Text Summarization

Keyphrase Generation: A Text Summarization Struggle

no code implementations29 Mar 2019 Erion Çano, Ondřej Bojar

Most of the proposed supervised and unsupervised methods for keyphrase generation are unable to produce terms that are valuable but do not appear in the text.

Text Summarization

Word Embeddings for Sentiment Analysis: A Comprehensive Empirical Survey

no code implementations2 Feb 2019 Erion Çano, Maurizio Morisio

This work investigates the role of factors like training method, training corpus size and thematic relevance of texts in the performance of word embedding features on sentiment analysis of tweets, song lyrics, movie reviews and item reviews.

Sentiment Analysis Word Embeddings

Hybrid Recommender Systems: A Systematic Literature Review

1 code implementation12 Jan 2019 Erion Çano, Maurizio Morisio

Also cold-start and data sparsity are the two traditional and top problems being addressed in 23 and 22 studies each, while movies and movie datasets are still widely used by most of the authors.

Accuracy Metrics Recommendation Systems

Sentiment Analysis of Czech Texts: An Algorithmic Survey

no code implementations9 Jan 2019 Erion Çano, Ondřej Bojar

In the area of online communication, commerce and transactions, analyzing sentiment polarity of texts written in various natural languages has become crucial.

Sentiment Analysis

Text-based Sentiment Analysis and Music Emotion Recognition

no code implementations6 Oct 2018 Erion Çano

Second, there are various uncertainties regarding the use of word embedding vectors: should they be generated from the same data set that is used to train the model or it is better to source them from big and popular collections?

Emotion Recognition Music Emotion Recognition +3

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