Language Independent Answer Prediction from the Web

Alejandro Figueroa, Günter Neumann

In: Proceedings of the FinTAL 5th International Conference on Natural Language Processing, Finland. International Conference on Natural Language Processing (ICON) 5th 8/2006.


This work presents a strategy that aims to extract and rank predicted answers from the web based on the eigenvalues of a specially designed matrix. This matrix models the strength of the syntactic relations between words by means of the frequency of their relative positions in sentences extracted from web snippets. We assess the rank of predicted answers by extracting answer candidates for three different kinds of questions. Due to the low dependence upon a particular language, we also apply our strategy to questions from four different languages: English, German, Spanish, and Portuguese.

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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence