In our weekly AKSW Colloquium, we present research, technologies and tools of the Semantic Web. The colloquium is open to the public and we welcome interested students, colleagues and industry partners to experience bleeding edge work-in-progress presentations and discussion rounds as well as talks by invited experts of our AKSW lecture series.
On Monday, October 21at 1.30 – 2.30 pm in Room P-702 (Paulinum), we will have presentations by Suresh Pokharel about Ontologies for farming in Nepal and by Didier Cherix about his master’s thesis about semi automatic error detection in ontologies (in german).
Furthermore, we would like to announce, that there is complimentary coffee and cake after the session. Bachelor and Master students will be able to get points for attendance.
“Ontology Based Data Access and Integration for Improving the Effectiveness of Farming in Nepal” by Suresh Pokharel, new PhD student
I am Suresh Pokharel and I am studying at the University of Leipzig. My background is a Master of Engineering in Information and Communications Technologies (2008–2010) from Asian Institute of Technology, Thailand. I did my master’s thesis on the topic “Web Forum Mining based on User Satisfaction” under the supervision of Professor Sumanta Guha. I have an Bachelor of Engineering in Computer (2001–2005) from Pokhara University, Nepal. I taught (Part Time) Data Mining, Artificial Intelligence, Project works, Database etc. in Nepal College of Information Technology, Nepal since Sept 2010 to 29 Sept 2013.
In AKSW, I am working on the topic “Ontology Based Data Access and Integration for Improving the Effectiveness of Farming in Nepal”. The objective of this research is to integrate the agriculture related data (weather, crop, soil, geo-spatial data) with the help of semantic web technology for getting the richer agriculture related information.
Ontologiemetriken zur Datenqualitätsverbesserung von Didier Cherix, Masterarbeit
Ich studiere an der Universität Leipzig, wo ich meine Bachelorarbeit über die Generierung von SPARQL queries geschrieben habe.
Nun stelle ich meine Masterarbeit vor. Diese behandelt die Entwicklung eines semi-automatisierten Verfahrens zur Entdeckung von potentiellen Fehlern in einer Ontologie.
Um potentiell fehlerhafte Instanzen zu finden, werden die Werte der verschiedenen Properties analysiert und in Metriken erfasst. Mittels dieser Metriken werden die einzelnen Instanzen einer Klasse geclustert und somit versucht, Fehler zu entdecken.
