Combining knowledge discovery, ontologies, annotations, and semantic wikis

Semantic Wikis provide an original and operational infrastructure for efficiently com- bining semantic technologies and collaborative design activities. This text presents: a running example and its context (organization of the collections in a museum); concepts of wikis as a tool to allow computer supported cooperative work (cscw); concepts of se- mantic technologies and knowledge representation; concepts and examples of semantic wikis; anatomy of a semantic wiki (reasoning tools, storage, querying); and research directions.Laboratorio de Investigación y Formación en Informática Avanzad

Indonesian Language Term Extraction using Multi-Task Neural Network

The rapidly expanding size of data makes it difficult to extricate information and store it as computerized knowledge. Relation extraction and term extraction play a crucial role in resolving this issue. Automatically finding a concealed relationship between terms that appear in the text can help people build computer-based knowledge more quickly. Term extraction is required as one of the components because identifying terms that play a significant role in the text is the essential step before determining their relationship. We propose an end-to-end system capable of extracting terms from text to address this Indonesian language issue. Our method combines two multilayer perceptron neural networks to perform Part-of-Speech (PoS) labeling and Noun Phrase Chunking. Our models were trained as a joint model to solve this problem. Our proposed method, with an f-score of 86.80%, can be considered a state-of-the-art algorithm for performing term extraction in the Indonesian Language using noun phrase chunking

Design Trend Forecasting by Combining Conceptual Analysis and Semantic Projections: New Tools for Open Innovation

[EN] In this paper, we describe a new trend analysis and forecasting method (Deflexor), which is intended to help inform decisions in almost any field of human social activity, including, for example, business, art and design. As a result of the combination of conceptual analysis, fuzzy mathematics and some new reinforcing learning methods, we propose an automatic procedure based on Big Data that provides an assessment of the evolution of design trends. The resulting tool can be used to study general trends in any field¿depending on the data sets used¿while allowing the evaluation of the future acceptance of a particular design product, becoming in this way, a new instrument for Open Innovation. The mathematical characterization of what is a semantic projection, together with the use of the theory of Lipschitz functions in metric spaces, provides a broad-spectrum predictive tool. Although the results depend on the data sets used, the periods of updating and the sources of general information, our model allows for the creation of specific tools for trend analysis in particular fields that are adaptable to different environments.This research was funded by Istituto Europeo di Design and Generalitat Valenciana, Cátedra de Transparencia y Gestión de Datos, Universitat Politècnica de València (PID2019-105708RBC21 (MICIU/FEDER,UE)).Manetti, A.; Ferrer Sapena, A.; Sánchez Pérez, EA.; Lara-Navarra, P. (2021). Design Trend Forecasting by Combining Conceptual Analysis and Semantic Projections: New Tools for Open Innovation. Journal of Open Innovation: Technology, Market, and Complexity. 7(1):1-26. https://doi.org/10.3390/joitmc7010092S1267

FROM USER-GENERATED-CONTENT TO STRUCTURED KNOWLEDGE EXPLORING MULTI-ASPECT SENTENCE REPRESENTATION AND PROTOTYPE HIERARCHY BASED CATEGORIZATION FOR ORGANIZATION OF TEXT COLLECTIONS

Ph.DDOCTOR OF PHILOSOPH