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We compare the use of überhaupt and sowieso in Dutch and German. We use the world-wide web as the main resource and pursue a zigzag strategy, trying to find usages going back and forth between dictionaries, intuitions and real data obtained through web search. To our surprise, the results more or less confirm the decision of Dutch dictionaries to consider überhaupt and sowieso synonymous. In German, we find no synonymy, but only a great overlap of usage conditions in declarative sentences.
From Proof Texts to Logic. Discourse Representation Structures for Proof Texts in Mathematics
(2009)
We present an extension to Discourse Representation Theory that can be used to analyze mathematical texts written in the commonly used semi-formal language of mathematics (or at least a subset of it). Moreover, we describe an algorithm that can be used to check the resulting Proof Representation Structures for their logical validity and adequacy as a proof.
The paper discusses particular logical consistency conditions satisfied by German proposition-embedding predicates which determine the question type (external and internal whether-form as well as exhaustive and non-exhaustive wh-form), the correlate type (es- or da-correlate) as well as the impact of the correlate on the respective consistency condition. It will turn out that some consistency conditions also determine the embedding of verb second and subject-control.
Beyond the stars: exploiting free-text user reviews to improve the accuracy of movie recommendations
(2009)
In this paper we show that the extraction of opinions from free-text reviews can improve the accuracy of movie recommendations. We present three approaches to extract movie aspects as opinion targets and use them as features for the collaborative filtering. Each of these approaches requires different amounts of manual interaction. We collected a data set of reviews with corresponding ordinal (star) ratings of several thousand movies to evaluate the different features for the collaborative filtering. We employ a state-of-the-art collaborative filtering engine for the recommendations during our evaluation and compare the performance with and without using the features representing user preferences mined from the free-text reviews provided by the users. The opinion mining based features perform significantly better than the baseline, which is based on star ratings and genre information only.