Update README.md

Author: Christian Schulz

README.md

@@ -4,7 +4,7 @@
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 [![FOSSA Status](https://app.fossa.com/api/projects/git%2Bgithub.com%2FDynGraphLab%2FDynMatch.svg?type=shield)](https://app.fossa.com/projects/git%2Bgithub.com%2FDynGraphLab%2FDynMatch?ref=badge_shield)
 
-In recent years, significant advances have been made in the design and analysis of fully dynamic maximal matching algorithms.  However, these theoretical results have received very little attention from the practical perspective. Few of the algorithms are implemented and tested on real datasets, and their practical potential is far from understood.  Here, we provide a start to bridge the gap between theory and practice that is currently observed for the fully dynamic maximal matching problem. We engineer several algorithms and empirically study those algorithms on an extensive set of dynamic instances. We provide an _overview talk_ over the algorithms contained in the framework [here](https://drive.google.com/file/d/1HMCTWshidkOCyDLB923CXELYYSBUddq8/view). If you just want to have a look at slides explaining the algorithms, you can click [here](https://drive.google.com/file/d/1rtv6jwSe4DD88sevEHLkG3ESVtcr9_ak/view?usp=sharing). Experimental results and indepth descriptions of the algorithms can be found [here](https://doi.org/10.4230/LIPIcs.ESA.2020.58).
+In recent years, significant advances have been made in the design and analysis of fully dynamic maximal matching algorithms.  However, these theoretical results have received very little attention from the practical perspective. Few of the algorithms are implemented and tested on real datasets, and their practical potential is far from understood.  Here, we provide a start to bridge the gap between theory and practice that is currently observed for the fully dynamic maximal matching problem. We engineer several algorithms and empirically study those algorithms on an extensive set of dynamic instances. We provide an _overview talk_ over the algorithms contained in the framework [here](https://drive.google.com/file/d/1HMCTWshidkOCyDLB923CXELYYSBUddq8/view). If you just want to have a look at slides explaining the algorithms, you can click [here](https://drive.google.com/file/d/1rtv6jwSe4DD88sevEHLkG3ESVtcr9_ak/view?usp=sharing). Experimental results and indepth descriptions of the algorithms can be found [here](https://doi.org/10.4230/LIPIcs.ESA.2020.58). 
 
 <p align="center">
 <img src="./img/matching2.png"