On November 1st 2019, Buma/Stemra and Sena started with MESLIS (Music-Event-System-Location-Ident-System) of deecoob Technology to maximize market coverage in the Dutch events sector. MESLIS is a cloud based IT-solution, an innovative self-learning system to automatically map events, locations, organizers, artists and setlists.
This week – from 20 to 25 October 2019 – Mandy Keck and Thomas Gründer from Technische Universität Dresden represent the VANDA team in Vancouver and participate at the international IEEE VIS conference, which is the worldwide largest and most important conference on Information Visualization, Visual Analytics and Scientific Visualization. The conference started on Sunday with many interesting and inspiring keynotes, talks and tutorials, such as Explainable AI, Visual Design and Analysis, and Visualizations for Machine Learning.
From 2017 until end of August 2019 deecoob was successfully working on the research project “RECAM”. This was a cooperation project between deecoob Technology GmbH and the Forensic Sience Investigation Lab at the University of Applied Sciences Mittweida (HSMW). The abbreviation “RECAM” stands for retrospektive event monitoring for computer forensic enlightenment of copyright misuse on the basis of publicly available digital media. The goal was to develop a technology for automated, computer-forensic investigation of use and misuse of copyrights at music events. The application uses web crawlers and full-text indexers and provides interfaces with Facebook, Instagram, Twitter, epaper, and Web pages. The purpose is to analyze, process, and qualify textual data from publicly available sources.
The industrial partners Mercateo AG, chemmedia AG and deecoob Technology GmbH, together with the Technische Universität Dresden (TUD), worked on the joint R&D project “Visual Analytics Interfaces for Big Data Environments – VANDA” in the period 2016 to 2019. The aim of this project was to address the so-called four “V´s” – Volume, Velocity, Variety and Veracity – as the challenge of Big Data driven interfaces and applications. The research work was carried out both in the backend area, i.e. the efficient processing of Big Data, and in the frontend, i.e. the intuitive visualization of Big Data. In the course of the project, best practice solutions for visualization and backend processes were researched, developed and implemented in the form of demonstrators.
In June 2019 we presented our research results at OUTPUT.DD and the 50 Years of university computer science education in Dresden celebration. OUTPUT.DD is the project presentation of the Faculty of Computer Science of the Technische Universität Dresden where research results are presented to the general public once a year.
In our continuous development of MESLIS WebApp during the last couple of weeks we set a strong focus on artist detection, event tags, data matching and key performance indicators.
MESLIS clients, collecting societies worldwide often need to know what artists performed on particular events to define the right license and correct amount of invoice for licensing those events. Some collecting societies even provide scores to individual artists to rank them. The web content extraction feature of MESLIS from now on automatically identifies and extracts all artist names from any digital, text based event description. These artist names are listed for sorting, searching, filtering and processing within a certain column and field in MESLIS WebApp. All users can search and filter for those artists and even select from an individually defined range of artist scores.
