6 papers
Leveraging Commonsense Knowledge on Classifying False News and Determining Checkworthiness of Claims
Ipek Baris Schlicht, Erhan Sezerer, Selma Tekir +2
Widespread and rapid dissemination of false news has made fact-checking an indispensable requirement. Given its time-consuming and labor-intensive nature, the task calls for an aut…
Bib2Auth: Deep Learning Approach for Author Disambiguation using Bibliographic Data
Zeyd Boukhers, Nagaraj Bahubali, Abinaya Thulsi Chandrasekaran +3
Author name ambiguity remains a critical open problem in digital libraries due to synonymy and homonymy of names. In this paper, we propose a novel approach to link author names to…
BiblioDAP: The 1st Workshop on Bibliographic Data Analysis and Processing
Zeyd Boukhers, Philipp Mayr, Silvio Peroni
Automatic processing of bibliographic data becomes very important in digital libraries, data science and machine learning due to its importance in keeping pace with the significant…
MexPub: Deep Transfer Learning for Metadata Extraction from German Publications
Zeyd Boukhers, Nada Beili, Timo Hartmann +2
Extracting metadata from scientific papers can be considered a solved problem in NLP due to the high accuracy of state-of-the-art methods. However, this does not apply to German sc…
ECOL: Early Detection of COVID Lies Using Content, Prior Knowledge and Source Information
Ipek Baris, Zeyd Boukhers
Social media platforms are vulnerable to fake news dissemination, which causes negative consequences such as panic and wrong medication in the healthcare domain. Therefore, it is i…
LaHAR: Latent Human Activity Recognition using LDA
Zeyd Boukhers, Danniene Wete, Steffen Staab
Processing sequential multi-sensor data becomes important in many tasks due to the dramatic increase in the availability of sensors that can acquire sequential data over time. Huma…