|Title||Automatic Domain Identification for Linked Open Data|
|Publication Type||Conference Paper|
|Year of Publication||2013|
|Authors||Sarasi Lalithsena, Prateek Jain, Pascal Hitzler, Amit Sheth|
|Conference Name||2013 IEEE/WIC/ACM International Conference on Web Intelligence|
|Conference Location||Atlanta, GA|
|Keywords||Dataset search, Domain Identification, Linked Open Data Cloud|
Linked Open Data (LOD) has emerged as one of the largest collections of interlinked structured datasets on the Web. Although the adoption of such datasets for applications is increasing, identifying relevant datasets for a specific task or topic is still challenging. As an initial step to make such identification easier, we provide an approach to automatically identify the topic domains of given datasets. Our method utilizes existing knowledge sources, more specifically Freebase, and we present an evaluation which validates the topic domains we can identify with our system. Furthermore, we evaluate the effectiveness of identified topic domains for the purpose of finding relevant datasets, thus showing that our approach improves reusability of LOD datasets.