Portfolio item number 1
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Posts by Collection
portfolio
Portfolio item number 2
Short description of portfolio item number 2
publications
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Paper Title Number 2
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Paper Title Number 3
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
research
Projects
Topics: Statistical Natural Language Processing, Social Network Analysis, Data Science, Sentiment Analysis, Big Data, and Web Mining.
Publications
Topics: Natural Language Processing, Statistical Natural Language Processing, Statistical Learning, Machine Learning, Social Network Analysis, Sentiment Analysis, Data Science, and Big Data.
software
Categorium
This package enables the creation and training of language models for text classification using BERT, with prescribed parameters for smaller dataset training. It also comprises six pre-trained models with 27 categories each for experimentation and a feature for testing out language models.
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ExtremeSentiLex
This Software was supported by National Founding from the FCT - Fundação para a Ciência e a Tecnologia. ExtremeSentilex is a lexicon of extreme sentiments created based on SentiWordNet and SenticNet we will soon provide an article where all the information of the research will be available. For now we have for download the file result of the research. One file with the lexicon and the classified datasets that we classified in order to validade our lexicon, a file with lexicon only and other with the classified datasets only.
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HULTIG-C: Cloud Platform for Computational Linguistics Services
This Software was supported by project C4 - Cloud Computing Competences Centre, financed by the P2020 HULTIG-C is a multilingual corpus, created to support research on information retrieval and related technologies of human language. HULTIG-C is characterized by various languages that include unique annotations such as keywords set, sentences set, named entity recognition set, and multiword set.
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HultigCrawler
This Software was supported by project C4 - Cloud Computing Competences Centre, financed by the P2020. HultigCrawler is a text crawler that crawls all the text from given website recursively. The crawled data is then saved as items. These items are URL, Title, Tags and Text. This data is then saved into database using scrapy pipelines.
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Multilingual Text Parser
Multilingual Text Parser is a web page through which you can obtain both syntactic and morphological analysis of a given text, to obtain these results were used python libraries such as Spacy and Nltk. For this first version it is only possible to analyze texts in Portuguese, French, Spanish and English.
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SENTAWEB
This Software was supported by National Founding from the FCT - Fundação para a Ciência e a Tecnologia. Senta Web aims to provide an online way of automatically extracting expressions formed by sequences of lexicographic units lexicographical units (e.g. characters, words, punctuation marks), contiguous or non-contiguous, that are as syntactic-semantic units, with their own meaning.
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SocialDictionary
This package aims to account for emojis in sentiment analysis, making sentiment analysis better when emojis are included in the text. First, we take the emojis from the ‘https://getemoji.com/’ website. We create a CSV with information about each emoji taken, such as the Unicode and description. We calculate the score of the emoji description and assign a sentiment, which can be positive, neutral, or negative. After this information, we use the EmoRoBERTa model, which uses GoEmotions to recognize emotions, so we then assign an emotion to each of the emojis on the list. Next, we place an input containing emojis, and then the text is returned with the emoji replaced by the emotion, the sentiment of the text, and information about the emoji/s used in the input.
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SocialNetCrawler
This Software was supported by project C4 - Cloud Computing Competences Centre, financed by the P2020. A crawler to extract data from social networks. This crawler was developed in Java programming language and our interface was done with Java Swing. To get started, you only need to visit the social networks developer pages our crawler works with, and follow the steps on the respective pages to get an access token. Then put that access token on our application in the tabs of each social network you want to crawl and press start.
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students
M.Sc. Students
Research Areas: Statistical Natural Language Processing, Statistical Learning, Machine Learning, Social Network Analysis, Sentiment Analysis, Data Science and Data Mining. The second cycle of studies leading to the Masters degree in Computer Engineering intends to form future engineers with a solid knowledge and the appropriate skills for the current labor market, as well as providing them with a basis for the frequency of the third cycle of studies (PhD) in Computer Engineering.
Ph.D. Students
Research Areas: Multimodal Mental Health Retrieval, Temporal Mental Health Retrieval. This PhD program allows the students that finish an MSc in Computer Science or similar, to proceed with their studies towards a PhD degree. The program has a PhD course with 60 ECTS credit units in the first year, and the research towards a PhD thesis in the following two years.
PostDoc Researcher
Research Areas: Natural Language Processing, Social Network Analysis, Sentiment Analysis, Big Data, Web Mining.
talks
Talk 1 on Relevant Topic in Your Field
Atualizado em:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Tutorial 1 on Relevant Topic in Your Field
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Talk 2 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Data Analytics
Artificial Intelligence and Data Science, University of Beira Interior, Computer Science Department, 2023
At the end of this course unit, the student is expected to be able to understand what data analysis is and how it fits into the data science workflow, recognizing the nature of different types of data and the need to process them appropriately.
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Computacional Logic
Computer Science and Engineering, Artificial Intelligence and Data Science & Mathematics and Applications, University of Beira Interior, Computer Science Department, 2024
This course presents the main concepts of Logic, in its computational aspect, i.e. through algorithms and computational techniques that allows its use in the field of Computer Engineering.
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Data Extraction and Transformation
Artificial Intelligence and Data Science, University of Beira Interior, Computer Science Department, 2024
Upon successful completion of the course, students should be able to: -Know and apply methods of extracting data from various sources; - Know how to apply data processing methodologies to improve data quality and establish consistency; - Know how to identify and use relational or non-relational databases data loading technologies.
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