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Minish HAT: A Tool for the Minimization of Here-and-There Logic Programs and Theories in Answer Set Programming
(M D P I AG, 2019-07-31)
[Abstract] When it comes to the writing of a new logic program or theory, it is of great importance to obtain a concise and minimal representation, for simplicity and ease of interpretation reasons. There are already a few ...
Novel and Diverse Recommendations by Leveraging Linear Models with User and Item Embeddings
(Springer, 2020-04-08)
[Abstract] Nowadays, item recommendation is an increasing concern for many companies. Users tend to be more reactive than proactive for solving information needs. Recommendation accuracy became the most studied aspect of ...
Using Discrete Wavelet Transform to Model Whistle Contours for Dolphin Species Classification
(M D P I AG, 2018-09-17)
[Abstract] This work proposes the use of features based on the discrete wavelet transform (DWT) for dolphin species classification. These features are compared with other previously used in the literature, and the experiments ...
Building High-Quality Datasets for Information Retrieval Evaluation at a Reduced Cost
(M D P I AG, 2019-08-01)
[Abstract] Information Retrieval is not any more exclusively about document ranking. Continuously new tasks are proposed on this and sibling fields. With this proliferation of tasks, it becomes crucial to have a cheap way ...
Priors for Diversity and Novelty on Neural Recommender Systems
(M D P I AG, 2019-07-31)
[Abstract] PRIN is a neural based recommendation method that allows the incorporation of item prior information into the recommendation process. In this work we study how the system behaves in terms of novelty and diversity ...
Designing an Open Source Virtual Assistant
(MDPI AG, 2020-08-21)
[Abstract]
A chatbot is a type of agent that allows people to interact with an information repository using natural language. Nowadays, chatbots have been incorporated in the form of conversational assistants on the most ...
Multiple-Choice Question Answering Models for Automatic Depression Severity Estimation
(MDPI, 2021)
[Abstract] Depression is one of the most prevalent mental health diseases. Although there are effective treatments, the main problem relies on providing early and effective risk detection. Medical experts use self-reporting ...
aspBEEF: Explaining Predictions Through Optimal Clustering
(MDPI AG, 2020-08-28)
[Abstract]
In this paper we introduce aspBEEF, a tool for generating explanations for the outcome of an arbitrary machine learning classifier. This is done using Grover’s et al. framework known as Balanced English ...
Delving into the Depths: Evaluating Depression Severity through BDI-biased Summaries
(Association for Computational Linguistics, 2024-03)
[Abstract]: Depression is a global concern suffered by millions of people, significantly impacting their thoughts and behavior. Over the years, heightened awareness, spurred by health campaigns and other initiatives, has ...
eRisk 2020: autolesiones y desafíos de la depresión
(Springer, 2020-04-08)
[Abstract] This paper describes eRisk, the CLEF lab on early risk prediction on the Internet. eRisk started in 2017 as an attempt to set the experimental foundations of early risk detection. Over the last three editions ...