Kategorie: Forschung & Entwicklung

Language Discourse in the context of Natural Language Processing – A Quick Look

Discourse takes various modalities, structures, and mediums. Among the commonly experienced mediums are face-to-face chats, telephone conversations, television news broadcasts, radio news, talk shows, lectures, books, and scientific articles. Intriguingly, each of these forms of discourse follow a logical structural nuance depending on the medium. The advancement of the digital age including social media communication has further led to expansion of logical discourse structures. These include blog-posts, emails, websites, review sites of products, hotels, restaurants or movies, and, finally, social media streams such as Twitter, Facebook, Reddit, #slack channels, Q&A portals such as Quora or Stack Overflow, etc., with a growing list as new mediums of communication over the World Wide Web are invented.
Large and varied streams of natural discourse only mean an even larger body of research questions remains to be explored!

Curtains for B!SON beta!

Researchers can now have thematically appropriate, quality-assured Open Access journals recommended for their manuscript: with the beta version of the B!SON recommendation system. All interested parties are cordially invited to give us feedback on the recommendations and usability. In addition to the call for testing, in the blog post we report on the development work in the project and explain how the recommendation algorithm works.

Vorhang auf für B!SON beta!

Wissenschaftler:innen können sich nun thematisch passende, qualitätsgesicherte Open-Access-Zeitschriften für ihr Manuskript empfehlen lassen: mit der Betaversion des Empfehlungssystems B!SON. Alle Interessierten sind herzlich dazu eingeladen, uns Feedback zu den Empfehlungen und zur Usability zu geben. Neben dem Aufruf zum Testen berichten wir im Blogbeitrag von der Entwicklungsarbeit im Projekt und erläutern, wie der Empfehlungsalgorithmus funktioniert.

NLP Should Go Beyond Commonsense Knowledge

NLP technology is all-pervasive for commonsense knowledge. There are many causes for this. Most of the internet and its data is about commonsense knowledge and world events, so NLP technology is developed over the data domain that is most easily available. But what about the scholarly domain with its rapidly growing body of knowledge produced worldwide? These are those specialized domains of knowledge in Science, Technology, Engineering, and Mathematics (STEM), all of which open up countless doors for NLP.

The opportunities are endless!

“Color comp” by Pablo Stanley

Project TAPIR: Harvesting the power of PIDs

In the TAPIR project, we are testing partially automated procedures for research reporting in the context of university and non-university research. We are investigating the extent to which the necessary data aggregation can be carried out on the basis of openly available research information using persistent identifiers.

“Color comp” by Pablo Stanley

Projekt TAPIR: Mit der Macht der PIDs

Im Projekt TAPIR erproben wir teilautomatisierte Verfahren zur Forschungsberichterstattung im Kontext universitärer und außeruniversitärer Forschung. Wir gehen der Frage nach, inwiefern die dazu erforderliche Datenaggregation auf Basis offen verfügbarer Forschungsinformationen mittels persistenter Identifikatoren durchgeführt werden kann.