Knowledge about the domain to be analyzed permeates all steps of the Knowledge Discovery process, from feature generation and selection to result interpretation and visualization. In most cases, this background knowledge resides in the data analyst’s mind only, but making it explicit would open new opportunities for knowledge discovery. We are currently witnessing a paradigm-shift: if once, encoding background knowledge was an arduous and mostly manual task, nowadays Semantic Web technologies are empowering the access to background knowledge in the form of ontologies and linked data. In this seminar, I will discuss the current state of the art in exploring the Semantic Web in Data Mining and Knowledge Discovery, and present research contributions in the areas of semantic integration and ontology matching, and semantic similarity and its applications to clustering.
Short Bio: Cátia Pesquita is an Assistant Professor at the Computer Science department at Faculdade de Ciências, Universidade de Lisboa. She is also a researcher at LASIGE where she leads research projects dedicated to several areas including the development of novel semantics based approaches to knowledge engineering and data mining, particularly in the biomedical and clinical domains. She has made significant contributions to the areas of ontology matching and ontology-based semantic similarity. Catia Pesquita has a degree in Biology, an MSc in Bioinformatics and a PhD in Computer Science, awarded by Universidade de Lisboa. She was the recipient of a research award from the Luso-American Foundation for Development. Together with her research team she has also won several awards and competitions in ontology matching.
