Open Access

We examine the task of relation extraction in the food domain by employing distant supervision. We focus on the extraction of two relations that are not only relevant to product recommendation in the food domain, but that also have significance in other domains, such as the fashion or electronics domain. In order to select suitable training data, we investigate various degrees of freedom. We consider three processing levels being argument level, sentence level and feature level. As external resources, we employ manually created surface patterns and semantic types on all these levels. We also explore in how far rule-based methods employing the same information are competitive.

We present an approach for modeling German negation in open-domain fine grained sentiment analysis. Unlike most previous work in sentiment analysis, we assume that negation can be conveyed by many lexical units (and not only common negation words) and that different negation words have different scopes. Our approach is examined on a new dataset comprising sentences with mentions of polar expressions and various negation words. We identify different types of negation words that have the same scopes. We show that already negation modeling based on these types largely outperforms traditional negation models which assume the same scope for all negation words and which employ a window-based scope detection rather than a scope detection based on syntactic information.

In the last years a common notion of a Problem-Solving Method (PSM) emerged from different knowledge engineering frameworks. As a generic description of the dynamic behaviour of knowledge based systems PSMs are favored subjects of reuse. Up to now, most investigations on the reuse of PSMs focus on static features and methods as objects of reuse. By this, they ignore a lot of information of how the PSM was developed that is, in principle, entailed in the different parts of a conceptual model of a PSM. In this paper the information of the different parts of PSMs is reconsidered from a reuse process point of view. A framework for generalized problem-solving methods is presented that describes the structure of a category of methods based on family resemblances. These generalized methods can be used to structure libraries of PSMs and - in the process of reuse - as a means to derive an incarnation, i.e. a member of its family of PSMs. For illustrating the ideas, the approach is applied to the task rsp. problem type of parametric design.