Summary: We present a series of innovative methods for a webbased multilingual question answering in open domains. In particular, we present novel strategies for the determination of optimal answer contexts and for the extraction of exact answers on the basis of language-independent, data-driven Machine Learning algorithms. Two alternative methods for the crosslingual question analysis are presented that are used for finding answers in documents of one natural language using a query formulated in another natural language. All methods are evaluated in detail and demonstrate a promising performance.