PPubMed14 Dec 2020Cited 1×

Selected articles from the Fourth International Workshop on Semantics-Powered Data Mining and Analytics (SEPDA 2019)

Zhe He, Cui Tao, Jiang Bian, Rui Zhang

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.

§ The Valyu brief

The paper, in five minutes

Read from the full text via Valyu Contents

The supplement showcases seven extended SEPDA 2019 papers demonstrating semantic methods for health data analytics across knowledge graphs, ontology analytics, and deep learning.

What’s new

i.Summarized and extended seven workshop papers from SEPDA 2019 into journal articles.
ii.Categorized the papers into three themes: Knowledge Graph, Ontology-Powered Analytics, and Deep Learning.
iii.Highlighted semantic methods such as knowledge‑graph generation, interpretable node classification, and ontology‑based data integration.
iv.Demonstrated applications addressing treatment effect prediction, PTSD detection, and biomedical relationship mining.

How they did it

Authors of selected workshop papers were invited to add experiments and detailed methods, then underwent two‑expert peer review and multiple revision rounds; the editorial then summarizes and groups the extended works.

What they found

Seven papers were accepted after rigorous peer review.
MINDWAL achieved competitive accuracy with improved interpretability for node classification in knowledge graphs.
The ADTEP model outperformed state‑of‑the‑art methods on two clinical datasets for treatment effect prediction.
The CNN‑based model with word embeddings surpassed baselines (NBC, SVM, MLP, CNN‑n‑grams) in classifying PTSD‑related tweets.
Rossanez et al.’s semi‑automatic NLP method showed reasonable performance generating ontology‑linked knowledge graphs.

§ The Valyu brief

Reading the full paper and taking notes. This takes a few seconds…

§ Ask this paper

Ask a question about this paper

Valyu reads the full text and answers from what the paper actually says.

§ Related work in other archives

Selected articles from the Fourth International Workshop on Semantics-Powered Data Mining and Analytics (SEPDA 2019)

The paper, in five minutes

Ask a question about this paper

Similar papers in all four archives

The paper, in five minutes

Similar papers in all four archives