https://hdl.handle.net/10481/13883 Sat, 11 Apr 2026 16:48:11 GMT 2026-04-11T16:48:11Z https://hdl.handle.net/10481/101707 Conversational human-machine interfaces Rodríguez-Sánchez, María Jesús; Benghazi, Kawtar; Griol, David; Callejas, Zoraida This chapter presents an overview of existing technology and methods for developing conversational human-machine interfaces. Specifically, current approaches for the development of dialogue systems are described, also focusing on the different objectives that the dialogues may have, either to solve particular tasks or to hold open chit-chat conversations. Additionally, research challenges are identified, providing an outlook for future conversational systems. https://hdl.handle.net/10481/101707 https://hdl.handle.net/10481/98066 Similarity Fuzzy Semantic Network for Social Media Analysis Castro Peña, Juan Luis; Francisco Aparicio, Manuel Microblogging sites are being used as analysis avenues due to their peculiarities (promptness, short texts...). Lately, researchers have focused mainly in classification performance rather than interpretability. When the problem requires transparency, it is necessary to build interpretable pipelines, and even though, resulting models are too complex to be considered comprehensible, making it impossible for humans to understand the actual decisions. This paper presents a feature selection mechanism that is able to improve comprehensibility by using less but more meaningful features. Results show that our proposal is better and the most stable one in terms of accuracy, generalisation and comprehensibility in microblogging context. https://hdl.handle.net/10481/98066 https://hdl.handle.net/10481/98065 Discriminatory Expressions to Improve Model Comprehensibility in Short Documents Castro Peña, Juan Luis; Francisco Aparicio, Manuel Microblogging sites are being used as analysis avenues due to their peculiarities (promptness, short texts...). Lately, researchers have focused mainly in classification performance rather than interpretability. When the problem requires transparency, it is necessary to build interpretable pipelines, and even though, resulting models are too complex to be considered comprehensible, making it impossible for humans to understand the actual decisions. This paper presents a feature selection mechanism that is able to improve comprehensibility by using less but more meaningful features. Results show that our proposal is better and the most stable one in terms of accuracy, generalisation and comprehensibility in microblogging context. https://hdl.handle.net/10481/98065 https://hdl.handle.net/10481/98064 Similarity Fuzzy Semantic Networks and Inference. An Application to Analysis of Radical Discourse in Twitter Castro Peña, Juan Luis; Francisco Aparicio, Manuel In this paper we introduce a new Knowledge Representation model, the Similarity Fuzzy Semantic Networks. It is an extension of Fuzzy Semantic Networks that incorporates reasoning by similarity through a Similarity Inference Rule. Moreover, we show as it can be effectively applied to a trending and complex problem like the analysis of radical discourse in Twitter. https://hdl.handle.net/10481/98064 https://hdl.handle.net/10481/77933 Social and Semantic Web Technologies for the Text-To-Knowledge Translation Process in Biomedicine Cano Gutiérrez, Carlos; Labarga, Alberto; Blanco Morón, Armando Currently, biomedical research critically depends on knowledge availability for flexible re-analysis and integrative post-processing. The voluminous biological data already stored in databases, put together with the abundant molecular data resulting from the rapid adoption of high-throughput techniques, have shown the potential to generate new biomedical discovery through integration with knowledge from the scientific literature. Reliable information extraction applications have been a long-sought goal of the biomedical text mining community. Both named entity recognition and conceptual analysis are needed in order to map the objects and concepts represented by natural language texts into a rigorous encoding, with direct links to online resources that explicitly expose those concepts semantics (see Figure 1). https://hdl.handle.net/10481/77933