Computerlinguistik
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Ziel dieses Projekts ist es, Sprachdaten so nah wie möglich am Jetzt zu erheben und analysierbar zu machen. Wir möchten, dass möglichst viele Menschen, nicht nur Sprachwissenschaftlerinnen und Sprachwissenschaftler, in die Lage versetzt werden, Sprachdaten zu explorieren und zu nutzen. Hierzu erheben wir ein Korpus, d. h. eine aufbereitete Sammlung von Sprachdaten von RSS-Feeds deutschsprachiger Onlinequellen. Wir zeichnen die Entwicklung der Analysewerkzeuge von einem Prototyp hin zur aktuellen Form der Anwendung nach, die eine komplette Reimplementierung darstellt. Dabei gehen wir auf die Architektur, einige Analysebeispiele sowie Erweiterungsmöglichkeiten ein. Fragen der Skalierbarkeit und Performanz stehen dabei im Mittelpunkt. Unsere Darstellungen lassen sich daher auf andere Data-Science-Projekte verallgemeinern.
Automatic summarization systems usually are trained and evaluated in a particular domain with fixed data sets. When such a system is to be applied to slightly different input, labor- and cost-intensive annotations have to be created to retrain the system. We deal with this problem by providing users with a GUI which allows them to correct automatically produced imperfect summaries. The corrected summary in turn is added to the pool of training data. The performance of the system is expected to improve as it adapts to the new domain.
The Leibniz-Institute for the German Language (IDS) was established in Mannheim in 1964. Since then, it has been at the forefront of innovation in German linguistics as a hub for digital language data. This chapter presents various lessons learnt from over five decades of work by the IDS, ranging from the importance of sustainability, through its strong technical base and FAIR principles, to the IDS’ role in national and international cooperation projects and its expertise on legal and ethical issues related to language resources and language technology.
In this paper we present work in developing a computerized grammar for the Latin language. It demonstrates the principles and challenges in developing a grammar for a natural language in a modern grammar formalism. The grammar presented here provides a useful resource for natural language processing applications in different fields. It can be easily adopted for language learning and use in language technology for Cultural Heritage like translation applications or to support post-correction of document digitization.
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.
We present a supervised machine learning AND system which tackles semantic similarity between publication titles by means of word embeddings. Word embeddings are integrated as external components, which keeps the model small and efficient, while allowing for easy extensibility and domain adaptation. Initial experiments show that word embeddings can improve the Recall and F score of the binary classification sub-task of AND. Results for the clustering sub-task are less clear, but also promising and overall show the feasibility of the approach.
The demo presents a minimalist, off-the-shelf AND tool which provides a fundamental AND operation, the comparison of two publications with ambiguous authors, as an easily accessible HTTP interface. The tool implements this operation using standard AND functionality, but puts particular emphasis on advanced methods from natural language processing (NLP) for comparing publication title semantics.
Lexical resources are often represented in table form, e. g., in relational databases, or represented in specially marked up texts, for example, in document based XML models. This paper describes how it is possible to model lexical structures as graphs and how this model can be used to exploit existing lexical resources and even how different types of lexical resources can be combined.
In this contribution we present some work of the R&D European project “LIRICS” and of the ISO/TC 37/SC 4 committee related to the topic of interoperability and re-use of language resources. We introduce some basic mechanisms of the standardization work in ISO and describe in more details the general approach on how to cope with the annotation of language data within ISO.