Bassa Kevin, Kern Roman, Kröll Mark
On-the-fly Data Set Generation for Single Fact Validation
SAC 2018, 2018
On the web, massive amounts of information are available, includingwrong (or conflicting) information. This spreading of erroneous or fake contentsmakes it hard for users to distinguish between what is true and what is not. Factfinding algorithms represent a means to validate information. Yet, these algorithmsrequire an already existing, structured data set to validate a single fact; anad-hoc validation is thus not supported making them impractical for usage in realworld applications. This work presents an approach to generate these data setson-the-fly. For three facts, we generate respective data sets and apply six state-ofthe-art fact finding algorithms for evaluation purposes. In addition, our approachcontributes to comparing fact finding algorithms in a more objective way.