FactCheck is a framework for the detection and resolution of conflicting structured data on the Web. The FactCheck framework is the result of ongoing research at our research group. One of the central building blocks is the context-dependent comparison of structured data of various representations of one and the same real world object or artefact. The comparison is guided by so called precision metrics which is a flexible and sophisticated technique for logically comparing structured data values. Precision metrics consist of logical predicates used to evaluate the comparison of structured data. Goal of the project is to design and implement an appropriate model for the representation of precision metrics, the construction of such precision metrics as well as the application of the metrics for evaluating the comparison of data values. Various precision metrics should be defined and compared using a test dataset of 900.000 entities. Results of the project are to be demonstrated by a running demo application.
Are you looking for more information about FactCheck? We will briefly introduce the subject after the obligatory preliminary meeting (Vorbesprechung). We will meet for P1/P2 at 02.03, around 9:30, and for SPBA at 06.03, at 10:30, in room 5.01 at Währingerstraße 29.
Provided to the students: existing implementation of framework, test dataset
Technologies: Web Services; Semantic Web technologies; LOD; Microformats; JSON-LD; AI Tools; Docker
Tags: FactCheck; Python; Databases; Azure Cloud Services; Docker; Klas; Precision Metrics
