Buscar
Mostrando ítems 1-8 de 8
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 ...
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 ...
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 ...
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 ...
Keyword Embeddings for Query Suggestion
(Springer, Cham, 2023-04)
[Abstract]: Nowadays, search engine users commonly rely on query suggestions to improve their initial inputs. Current systems are very good at recommending lexical adaptations or spelling corrections to users’ queries. ...
Experimental Analysis of the Relevance of Features and Effects on Gender Classification Models for Social Media Author Profiling
(SCITEPRESS, 2021)
[Abstract] Automatic user profiling from social networks has become a popular task due to its commercial applications
(targeted advertising, market studies...). Automatic profiling models infer demographic characteristics
of ...