Author(s): Pinto, José Pedro ; Viana, Paula ; Teixeira, Inês ; Andrade, Maria
Date: 2022
Persistent ID: http://hdl.handle.net/10400.22/21674
Origin: Repositório Científico do Instituto Politécnico do Porto
Subject(s): Natural language processing; Machine learning; Multimedia systems; Context awareness; Word2Vec
The subjectiveness of multimedia content description has a strong negative impact on tag-based information retrieval. In our work, we propose enhancing available descriptions by adding semantically related tags. To cope with this objective, we use a word embedding technique based on the Word2Vec neural network parameterized and trained using a new dataset built from online newspapers. A large number of news stories was scraped and pre-processed to build a new dataset. Our target language is Portuguese, one of the most spoken languages worldwide. The results achieved significantly outperform similar existing solutions developed in the scope of different languages, including Portuguese. Contributions include also an online application and API available for external use. Although the presented work has been designed to enhance multimedia content annotation, it can be used in several other application areas.
