Selected articles from the Fourth International Workshop on Semantics-Powered Data Mining and Analytics (SEPDA 2019)
- PDF / 742,888 Bytes
- 4 Pages / 595.276 x 790.866 pts Page_size
- 87 Downloads / 178 Views
Open Access
INTRODUCTION
Selected articles from the Fourth International Workshop on Semantics‑Powered Data Mining and Analytics (SEPDA 2019) Zhe He1*, Cui Tao2, Jiang Bian3 and Rui Zhang4
From The 4th International Workshop on Semantics-Powered Data Analytics Auckland, New Zealand. 27 October 2019
Abstract In this introduction, we first summarize the Fourth International Workshop on Semantics-Powered Data Mining and Analytics (SEPDA 2019) held on October 26, 2019 in conjunction with the 18th International Semantic Web Conference (ISWC 2019) in Auckland, New Zealand, and then briefly introduce seven research articles included in this supplement issue, covering the topics on Knowledge Graph, Ontology-Powered Analytics, and Deep Learning. Background In the era of big data, the volume, the variety, as well as the velocity of data being generated have posed major challenges for people to leverage multiple data sets for decision making [1]. Ontologies and semantic standards have been widely used to tackle some of the challenges in big data analytics such as data integration and knowledge discovery [2]. In the biomedical domain, ontologies and controlled vocabularies are a cornerstone for health information systems including clinical decision support systems and electronic health record (EHR) systems [2, 3]. Moreover, rich vocabularies and semantic information embedded in the ontologies have been leveraged to extract clinically meaningful information from heterogenous data from various sources. In particular, they are instrumental in natural language processing and text mining [4]. As a notable example, the Unified Medical *Correspondence: [email protected] 1 School of Information, College of Communication and Information, Florida State University, 142 Collegiate Loop, Tallahassee, FL 32306‑2100, USA Full list of author information is available at the end of the article
Language System, developed and maintained by the U.S. National Library of Medicine, has been widely used in informatics research and applications using data in social media, scientific literature, and EHRs [5]. Applications like PubMed, which uses the UMLS indirectly, has been used by millions of users worldwide for biomedical research. The International Workshop on Semantics-Powered Data Mining and Analytics (SEPDA) has been established as an important venue for experts to discuss semantic-based methods and applications in health data analytics [6–8]. To continue our momentum, SEPDA 2019 was held on October 26, 2019, in conjunction with the 18th International Semantic Web Conference (ISWC 2019). Submissions were solicited on the topics including Semantics-Based Data Mining and Analytics, Ontologies and Controlled Vocabularies, Data Integration, and Applications. After the peer review by the program committee members, 11 papers were accepted for presentation and publication in the SEPDA 2019 workshop proceedings [9]. After the workshop, the authors of seven selected papers were invited to extend their workshop papers to journal papers by adding additional
Data Loading...
