OpenScience Initiative am IfI
Sammlung an OpenScience Projekten des Instituts für Informatik Frankfurt in den Kategorien:
OpenData, OpenAccess, OpenMethodology, OpenEducationalResources, CitizenScience, OpenSource.
OpenScience Initiative at IfI
Collection of OpenScience projects of the Institute for Computer Science Frankfurt in the categories:
OpenData, OpenAccess, OpenMethodology, OpenEducationalResources, CitizenScience, OpenSource.
OpenSource
This web application provides a service for an automated subgroup fairness analysis of a binary classifier. Our system detects the subgroups in the data automatically by using either subgroups obtained from clustering the dataset or entropy-based patterns derived from the found clusters.Contact: Prof. Dr. Lena Wiese
OpenAccess, OpenSource
Column family stores are a special case of NoSQL databases. To achieve data protection while at the same time supporting advanced data management in these stores, novel cryptographic algorithms like order-preserving and searchable encryption schemes are needed. In this project, several such schemes are implemented and tested with the stores Apache HBase and Apache Cassandra.Contact: Prof.Dr. Lena Wiese
OpenData
This benchmark suite presented at the FAC'14 conference is a collection of analog circuits with testbenches and device models, that are interesting for formal circuit verification.Contact: Prof.Dr. Lars Hedrich
OpenData, OpenMethodology, OpenSource
GerParCor is a genre-specific corpus of (predominantly historical) German-language parliamentary protocols from three centuries and four countries, including state and federal level data. In addition, GerParCor contains conversions of scanned protocols and, in particular, of protocols in Fraktur converted via an OCR process based on Tesseract. All protocols were preprocessed by means of the NLP pipeline of spaCy3 and automatically annotated with metadata regarding their session date. GerParCor is made available in the XMI format of the UIMA project. In this way, GerParCor can be used as a large corpus of historical texts in the field of political communication for various tasks in NLP.
Contact: Prof.Dr. Alexander Mehler
OpenSource
The Gnucap-UF extensions allow advanced methods for circuit analysis and verification. e.g. equivalence checking, state space analysis, ageing simulation.Contact: Prof.Dr. Lars Hedrich
OpenAccess, OpenSource
Contact: Prof.Dr. Lena Wiese
Contact: Prof.Dr. Alexander Mehler
OpenSource
SemioGraph aims to encode as much information as possible in one and the same graph representation. This is interesting for word networks, for example, where one needs to visualize units of information such as POS, node weight, node saliency, node centrality, etc. To present SemioGraph, we use word embedding networks.Contact: Prof.Dr. Alexander Mehler
OpenData
The Text Technology Lab provides on this page a list of ready-made embeddings created by the Lab. The list contains a variety of downloadable embeddings of different methods and parameters. Metadata is available for all files, with information about the corpus, the method, the tool hyper parameters and much more. This allows a detailed search and easy recovery as well as the reuse of the embedding files. All data is also available through a RESTful API.Contact: Prof.Dr. Alexander Mehler
Contact: Prof.Dr. Alexander Mehler
Contact: Prof.Dr. Alexander Mehler
OpenData, OpenMethodology, OpenSource
The collection of all UIMA TypeSystemDescriptors for the pipelines UIMA pipelines of the Text Technology.
Contact: Prof.Dr. Alexander Mehler
OpenSource
A collection of useful tools and classes for everyday use in the context of text technology.
Contact: Prof.Dr. Alexander Mehler
OpenEducationalResources, OpenSource
Bei algo-learn handelt es sich um ein Lernportal, das sich derzeit in einer frühen Entwicklungs- und Testphase befindet. Ein Prototyp kann bereits betrachtet werden: https://tcs.uni-frankfurt.de/algo-learn/. Das Projekt wird unter einer Open Source Lizenz entwickelt, daher nehmen wir pull requests, feature requests, sowie bug reports gerne auf GitHub entgegen.Contact: Prof. Dr. Holger Dell
OpenSource
An Efficient Word Sense Disambiguation Classifier
Contact: Prof.Dr. Alexander Mehler